<p data-start="0" data-end="375">AI hiring in the UK is moving fast - and 2026 is shaping up to be a defining year for startups and the engineers building them. Demand for AI capability is spreading across every sector and the talent market remains intensely competitive. In a world like this, guessing compensation or hiring strategy isn&rsquo;t enough. You need a benchmark.</p>
<p data-start="377" data-end="742">The <strong data-start="381" data-end="420">UK AI Engineering Salary Guide 2026</strong> is our most complete view of what&rsquo;s happening in the Vertical AI Applications Startup market right now. Built from thousands of data points across salary surveys, placement outcomes, and nearly 5,000 AI job adverts, giving you an inside track on how teams are paying, hiring, and scaling technical talent across the UK.</p>
<p data-start="744" data-end="777">Inside the guide you&rsquo;ll discover:</p>
<p data-start="780" data-end="965"><strong data-start="780" data-end="807">✅Compensation benchmarks</strong>&nbsp;<br><strong data-start="968" data-end="1003">✅Equity insights for early hires</strong><br><strong data-start="1065" data-end="1099">✅The hiring trends shaping 2026</strong><br><strong data-start="1197" data-end="1229">✅Role-by-role talent insights</strong><br><strong data-start="1369" data-end="1408">✅Practical, startup-focused guidance</strong>&nbsp;</p>

UK Salary Guide Form 2026

<p>Your data-led guide to salary benchmarks, recruitment insights, and hiring trends in UK AI.</p>

<p>UK AI Engineering Salary Guide 2026</p>

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UK AI Engineering Salary Guide 2026

<p dir="ltr">Any founder knows that building an AI model is only the beginning. The real test is turning technical innovation into a usable product that scales.</p>
<p dir="ltr">Across the Faces of AI series, founders shared the toughest parts of that journey - from market readiness and regulation to maintaining alignment as their teams and products grow. Their stories show that success depends as much on people and process as it does on the model itself.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">1. From Proof of Concept to Product</h3>
<p>&nbsp;</p>
<h3 dir="ltr">Katya Lait, nettle</h3>
<p dir="ltr">Scalability isn't top of mind yet. We&rsquo;re still in our first year, building bespoke versions of nettle for clients. Year Two is when we&rsquo;ll step back, consider the ecosystem of solutions we&rsquo;ve built, and focus on scalability.</p>
<p dir="ltr">Some obvious steps we&rsquo;re taking now are distributing requests across specialised agents, reducing unnecessary API calls, and building generic components we&rsquo;ll reuse across clients. As much as we can, we cache everything and have the system learn from itself - a crucial feature for our mission to close the knowledge gap in risk engineering.</p>
<p dir="ltr">Beyond data sovereignty and open-source innovation, the biggest challenge has been translation. We&rsquo;re working in a country where English isn&rsquo;t spoken, so our AI reasons in English but delivers results in the user&rsquo;s language. It&rsquo;s complex, but it means we can support virtually any market moving forward.</p>
<h3 dir="ltr">&nbsp;</h3>
<h3 dir="ltr">George Parry &amp; Charles Cross, Emma AI</h3>
<p dir="ltr">George: Our hardest technical challenge was building a system where any user can ask any question, about any part of their data, at any time, and get the right output. Interoperability in health and social care was another major hurdle. Too many companies treat patient data as their moat - even though it belongs to the user. We&rsquo;ve worked to make Emma the opposite: an open platform anyone can connect to and from.</p>
<p dir="ltr">Charles: Another challenge has been bridging the gap between initial excitement around AI and real-world impact. In a regulated, human-centred sector like care, plug-and-play tools don&rsquo;t work. Our partnership model means working closely with providers, iterating fast, and being open to tough conversations.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">Eric Marcuson, ClinBI</h3>
<p dir="ltr">For most founders, one of the biggest challenges is figuring out what customers actually want. Product&ndash;market fit isn&rsquo;t something you check off and move on from. It evolves - as channels, customer value, and priorities shift.</p>
<p dir="ltr">The other big challenge is people. Whether it&rsquo;s your team or your customers, understanding how people think, communicate, and collaborate is critical. That means always talking to the customer and those around them.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">Patrick Sharpe, Artificial Societies</h3>
<p dir="ltr">What we&rsquo;re building is unique - there aren&rsquo;t many prosumer tools that let people run real experiments. One of the biggest challenges has been making that experience accessible without dumbing it down.</p>
<p dir="ltr">Early on, there&rsquo;s a temptation to overbuild. But we&rsquo;ve had to practise real restraint. Our mantra is that simplicity is the ultimate sophistication.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">2. Bridging the Gap Between Tech and Adoption</h3>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">Eduardo Mandela, Maihem</h3>
<p dir="ltr">The biggest challenge (and opportunity) is the gap between cutting-edge AI and real-world adoption. Most companies don&rsquo;t have the talent, understanding, or confidence to use these tools effectively.</p>
<p dir="ltr">I call this the &lsquo;chasm of adoption&rsquo;. That&rsquo;s where we come in - bridging the gap through education, helping people understand how AI systems work and how to use them safely and effectively.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">George Hancock &amp; Eric Topham, Octaipipe</h3>
<p dir="ltr">George: We&rsquo;ve always been slightly ahead - building solutions 18 months before the market&rsquo;s really ready for them. The challenge isn&rsquo;t whether AI can help; it&rsquo;s whether the market recognises the problem it&rsquo;s solving right now.</p>
<p dir="ltr">Eric: 99% of people talking about AI don&rsquo;t really know what they&rsquo;re talking about. That makes scaling difficult because most organisations don&rsquo;t know what they&rsquo;re buying or how to be ready for it. You can build a brilliant churn prediction model, but if the business doesn&rsquo;t know what to do with that prediction, it&rsquo;s useless.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">Roshan Tamil Sellvan, AdvisoryAI</h3>
<p dir="ltr">It&rsquo;s important to set clear ethical boundaries, especially in finance. We&rsquo;ve built safeguards into our model architecture - training the AI to filter inappropriate language and analyse outputs against FCA frameworks before deployment. Multiple specialised models validate accuracy and compliance at each step. If a report doesn&rsquo;t meet quality thresholds, the system prompts a rewrite.</p>
<p dir="ltr">We started out building an assistant, but realised we&rsquo;d created a powerful report-writing tool. That adaptability has opened new markets - from finance to law. We&rsquo;re now expanding into the US, Australia, and Canada, each with its own regulations and nuances, but that&rsquo;s part of the challenge we&rsquo;re tackling as we grow.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">3. Scaling Without Losing What Works</h3>
<p>&nbsp;</p>
<h3 dir="ltr">Jonathan Low, Scope</h3>
<p dir="ltr">We've taken a modular approach to development because most inspection workflows are unique. As we scale, the challenge is keeping the data layer consistent so we can onboard customers faster and make it easier for them to adjust their reports and workflows.</p>
<p dir="ltr">As a small team, we've stayed very customer-focused. The goal is to keep that mindset - ensuring everyone on the team maintains the same level of customer involvement as we grow.</p>
<p><strong>&nbsp;</strong></p>
<h3 dir="ltr">Scott Wilson, Covecta</h3>
<p dir="ltr">Our biggest challenge - and it&rsquo;s ongoing - is scaling while maintaining impact and quality. As we work with more customers, the volume and complexity of product requirements increase.</p>
<p dir="ltr">We&rsquo;re focused on prioritising the features that deliver the greatest value to users and building an engineering engine that consistently ships high-quality AI capabilities at scale.</p>
<p dir="ltr">&nbsp;</p>
<hr>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">Once the model works, the real work begins.&nbsp;</p>
<p dir="ltr">Productising AI means navigating regulation, readiness, and human behaviour - all while proving value at scale. These founders show that lasting impact comes not just from technical excellence, but also from from clarity, adaptability, and a focus on real-world use.</p>
<p data-start="653" data-end="727"><strong>Generative connects top AI talent with the startups defining the future.</strong></p>
<p data-start="734" data-end="882"><a href="https://myfractional.ai/insider-channel/" target="_blank" rel="noopener"><strong data-start="734" data-end="762">Join our insider network</strong> to get first access to opportunities, stories, and trends from across the AI sector.</a></p>

Any founder knows that building an AI model is only the beginning. The real test is turning technical innovation into a usable product that scales.

You’ve Built the Model. Now What? The Hardest Part of Productising AI

<p dir="ltr">When your success hinges on how your message lands, why wait until after you&rsquo;ve launched to find out how it performs?&nbsp;</p>
<p dir="ltr">That&rsquo;s the question driving Artificial Societies, a startup using AI simulations to help founders, marketers, and decision-makers test how their content will resonate before it goes live.</p>
<p dir="ltr">In this edition of Faces of AI, we speak to Patrick Sharpe, co-founder and Chief Product Officer, about why behavioural science was the perfect launchpad, what makes their platform tick under the hood, and how AI is turning once-exclusive research tools into something far more accessible (and powerful) for everyday creators.</p>
<h3 dir="ltr">What specific problem is Artificial Societies solving, and why does it matter?</h3>
<p dir="ltr">We&rsquo;re solving a core problem: people don&rsquo;t know how their messages or ideas will land until they&rsquo;re already out in the world.</p>
<p dir="ltr">That matters because it&rsquo;s a high-stakes environment to get things wrong, especially when you're launching something new. We give people the confidence to take bigger bets by showing them how their communications are likely to be received before they go live.</p>
<h3 dir="ltr">What's the origin story behind the company?</h3>
<p dir="ltr">There are two of us behind Artificial Societies &ndash; myself and my co-founder, James. We&rsquo;re both behavioural scientists by background. I came from a behavioural economics and consulting path, where I was helping businesses run experiments to improve things like retention and conversion. The main problem there is that experiments tend to be slow, expensive, and sometimes impossible to run.</p>
<p dir="ltr">James came from a more theoretical background &ndash; network science and simulations. When he showed me what&rsquo;s possible by connecting AI agents to mimic real people, it clicked. This could be a faster, more scalable way to test ideas before going live.</p>
<p dir="ltr">We&rsquo;d known each other for a while, but in September last year, we started building. I immediately saw the product potential and how powerful this could be for decision-makers. That&rsquo;s where it all began.<strong><br></strong></p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/dee23eaa-1737-4c46-994b-15103a2b7f64" alt="" width="600" height="400"></p>
<h3 dir="ltr">There is a lot of uncertainty, even fear, in the wider population when it comes to AI. What are some of the most common myths or misconceptions that you hear?</h3>
<p dir="ltr">A big one is the fear that AI is replacing people or taking jobs. But what we&rsquo;re doing with Artificial Societies is actually expanding access, especially in market research.</p>
<p dir="ltr">Traditionally, running a survey with a few thousand people could cost $10,000 or more. That&rsquo;s only accessible to organisations with big budgets and long timelines. But everyone benefits from better audience understanding and more confident decision-making.</p>
<p dir="ltr">By using simulations, we lower the barrier to entry. Now, even something as simple as a LinkedIn post can be tested before going live. What used to be expensive and slow is now fast, affordable, and scalable. In that sense, we&rsquo;re aiming to be the ChatGPT of simulations by bringing cutting-edge tools to a much wider audience.</p>
<h3 dir="ltr">For you and the team at Artificial Societies, how does AI safety show up in your day to day?</h3>
<p dir="ltr">AI safety shows up in two big ways for us: data use and moderation.</p>
<p dir="ltr">First, we only use publicly available data: things people have freely posted online. For example, if this interview ends up on the internet, that&rsquo;s the kind of content we&rsquo;d use to build a persona of me. We don&rsquo;t collect private or sensitive information, and we&rsquo;re strict about what goes in.</p>
<p dir="ltr">Second, we&rsquo;ve put clear guardrails in place around how simulations can be used. You can create audiences like &ldquo;US professionals,&rdquo; but if someone tries to simulate an inappropriate or harmful group, it&rsquo;s automatically blocked.</p>
<p dir="ltr">What&rsquo;s powerful is that AI also helps us enforce these standards. Rather than relying on rigid rule sets or thousands of human moderators, our system uses AI to assess whether audience requests are appropriate. That allows us to moderate at scale &ndash; safely and responsibly.</p>
<h3 dir="ltr">What is the most exciting technical challenge that you've overcome so far?</h3>
<p dir="ltr">As Chief Product Officer, my focus is on how users interact with the product&hellip; what features they need, how intuitive it feels, and how we make something complex feel simple.</p>
<p dir="ltr">What we&rsquo;re building is pretty unique. There aren&rsquo;t many prosumer tools out there that let people run real experiments. So one of the biggest technical challenges has been making that experience accessible, without dumbing it down.</p>
<p dir="ltr">Early on, like most startups, there&rsquo;s a temptation to overbuild. But we&rsquo;ve had to practise real restraint. Our mantra is that simplicity is the ultimate sophistication.</p>
<p dir="ltr">From the user&rsquo;s perspective, it&rsquo;s straightforward: you describe who you want to simulate, and we do the rest. Behind the scenes, though, it&rsquo;s deeply complex. That one description gets enriched with AI, matched against a database of half a million personas, and turned into a functioning simulated society.</p>
<p dir="ltr">It's like an iceberg &ndash; the interface looks clean and minimal, but there's a huge technical structure beneath the surface. Making that invisible complexity feel natural to the user has been a major (and rewarding) challenge.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/ce7b95a7-6fbe-4ac9-8bdd-9a4f741eac26" alt="" width="600" height="400"></p>
<h3 dir="ltr">How people are using the product right now? What&rsquo;s the use case?</h3>
<p dir="ltr">One of the best current use cases for our product is in marketing. If you have a specific target audience and content like LinkedIn posts, emails, or blogs, our tool lets you simulate how that content will land before you launch it.</p>
<p dir="ltr">You can create detailed audiences &ndash; even hard-to-reach groups like CEOs, who rarely respond to traditional surveys. With simulations, you can effectively &ldquo;survey&rdquo; these groups and see their likely reactions.</p>
<p dir="ltr">It&rsquo;s ideal for content creators, marketers, founders&hellip; anyone with a message they want to resonate with the right people. We&rsquo;re excited to be launching new features soon, and we hope more people will give it a try!</p>
<h3 dir="ltr">In terms of AI trends, what are you finding genuinely exciting at the moment?</h3>
<p dir="ltr">What excites me most is how AI is lowering the barrier to entry for creative, technical work. Tools like Lovable and Cursor are great examples. You used to need years of engineering experience to build software or run data analysis. Now, with the right mindset and a bit of creativity, you can do those things in minutes.</p>
<p dir="ltr">It&rsquo;s not about replacing skills, but supercharging people who are already capable and curious. That&rsquo;s incredibly powerful.</p>
<p dir="ltr">I&rsquo;m also really interested in where UI is heading. Many products are becoming more complex under the hood, but with AI agents acting on your behalf, the user experience can stay simple and conversational. You won&rsquo;t need to learn a new system each time. You&rsquo;ll just tell the AI what you want to do, and it&rsquo;ll handle the complexity. That shift is going to make once-specialised skills feel native and intuitive, which is really exciting.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/632e6ea7-cd3c-4e61-b5e8-dc2ab61d7437" alt="" width="600" height="530"></p>
<h3 dir="ltr">Outside of work, how do you decompress?&nbsp;</h3>
<p dir="ltr">It&rsquo;s especially important for us to find balance, since James and I live and work in the same space &ndash; our flat is also our office. My commute is three metres down the hall, which is great for productivity, but it makes setting boundaries even more crucial.</p>
<p dir="ltr">For me, routines are everything. I&rsquo;ve made a rule that every morning before 9am is my time. No meetings. No work. Just some form of exercise. Whether it&rsquo;s a run, gym, yoga or stretching, I do it every single day. It&rsquo;s a non-negotiable.</p>
<p dir="ltr">That idea of setting defaults comes from behavioural science. It&rsquo;s much easier to follow through when you&rsquo;ve already decided in advance. It takes the mental load out of making the choice every day.</p>
<p dir="ltr">My girlfriend and I also have a weekly date-night rule. We take turns planning it and stick to it without fail. It&rsquo;s a simple way to protect time for each other outside of work.<strong><br></strong></p>
<h3 dir="ltr">If you weren't working on Artificial Societies, what other problems could you see yourself trying to solve with AI?</h3>
<p dir="ltr">Since starting the company, I&rsquo;ve got into the habit of journalling every night before bed. It helps me process the day and over time, it&rsquo;s become a way to track the whole journey.</p>
<p dir="ltr">The thing is, our memories &ndash;&nbsp;photos, journals, conversations &ndash; end up scattered across different places. One idea I&rsquo;d love to explore is an AI-powered memory bank. Something that could take all those daily reflections, photos, stories and turn them into a rich, narrative archive.</p>
<p dir="ltr">Imagine being able to talk to an AI at the end of each day, share what happened, have it prompt you, organise the moments, even pull in photos. Then, years down the line, you could ask it: what was it really like building that startup? And it would remember. Accurately, and in detail.</p>
<p dir="ltr">We forget so many of the little stories that make up a life. I&rsquo;d love to help people capture and tell them better.</p>
<p><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p id="ember704" class="ember-view reader-text-block__paragraph"><strong>Patrick and Artificial Societies were recently featured in our 'Faces of AI 2025' report, which is available to </strong><a class="TAkGWjHhmVmkmMDJGaNOrxvCVcOPkgho " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now</strong></a><strong>.</strong></p>
<p id="ember705" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="TAkGWjHhmVmkmMDJGaNOrxvCVcOPkgho " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link=""><strong>let's talk.</strong></a></p>

When your success hinges on how your message lands, why wait until after you’ve launched to find out how it performs?  That’s the question driving Artificial Societies, a startup using AI simulations to help founders, marketers, and decision-makers test how their content will resonate before it goes live.

Meet “The ChatGPT of Simulations” – How Artificial Societies Is Democratizing Market Testing

<h2 id="ember3781" class="ember-view reader-text-block__heading-3">Scott Wilson, Founder of Covecta, isn&rsquo;t here to hype AI. He&rsquo;s here to make it work.</h2>
<p id="ember3782" class="ember-view reader-text-block__paragraph">With a mission to unlock scalable growth in one of the world&rsquo;s most complex industries, <a class="EaWzLdfjwgloMRCqeXHrsnLLcqdpxKtzA " tabindex="0" href="https://www.linkedin.com/company/covecta/" data-test-app-aware-link="">Covecta</a> is building autonomous AI agents tailored for financial services.</p>
<p id="ember3783" class="ember-view reader-text-block__paragraph">In this conversation, Scott shares what it really takes to scale AI at the enterprise level, why human oversight is evolving &ndash; and why now&rsquo;s the time to join the team shaping the agentic layer of the future.</p>
<h2>What specific problem is your startup solving and why does it matter right now more than ever?</h2>
<p id="ember3785" class="ember-view reader-text-block__paragraph">We&rsquo;re solving a widespread productivity and growth challenge in financial services.</p>
<p id="ember3786" class="ember-view reader-text-block__paragraph">In many Western economies, productivity has stagnated &ndash; largely because organisations haven&rsquo;t modernised their tech infrastructure fast enough. Instead, they&rsquo;ve leaned on growing headcount, which only adds cost without addressing the underlying issues.</p>
<p id="ember3787" class="ember-view reader-text-block__paragraph">Our AI agents are purpose-built for financial services. They help optimise operating models and redirect investment toward technology that enables scalable, sustainable growth.</p>
<p id="ember3788" class="ember-view reader-text-block__paragraph">And why now? Over the past three years, we&rsquo;ve seen rapid AI adoption. What started with ChatGPT&rsquo;s consumer-level impact has evolved into mature enterprise capabilities &ndash; both generative and agentic. Every organisation is now asking: how can we use AI to strengthen our competitive edge, accelerate growth, and operate more efficiently?</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/122a8962-53c0-4af7-97e6-23b4abdacba3" alt="" width="600" height="412"></p>
<h2 id="ember3790" class="ember-view reader-text-block__heading-2">What's the origin story behind Covecta?</h2>
<p id="ember3791" class="ember-view reader-text-block__paragraph">Covecta&rsquo;s founders have backgrounds in financial services and enterprise technology. We&rsquo;ve seen the challenges in this space firsthand and have worked together long enough to build the trust and understanding that&rsquo;s essential for starting a business.</p>
<p id="ember3792" class="ember-view reader-text-block__paragraph">We believe the opportunity here is huge. And if we get it right, we&rsquo;ll unlock value not just for the industry, but for Covecta and our team as well.</p>
<h2 id="ember3794" class="ember-view reader-text-block__heading-2">There is a lot of uncertainty within the wider population when it comes to AI. What are some of the most common misconceptions you hear?</h2>
<p id="ember3795" class="ember-view reader-text-block__paragraph">There&rsquo;s a common fear that AI will replace humans, but history tells us otherwise.</p>
<p id="ember3796" class="ember-view reader-text-block__paragraph">The same fears surfaced with the industrial revolution and the internet. Each time, rather than eliminating human roles, technology shifted the nature of work. AI is no different. It&rsquo;s here to augment human capabilities, and not always replace them.</p>
<p id="ember3797" class="ember-view reader-text-block__paragraph">Yes, we will see disruption across labour markets, but I don't think in the immediate term we are going to see mass lay-offs. What we&rsquo;ll see is a rebalancing: people moving into roles where they can be most effective, just as we have in every major technological shift.</p>
<p id="ember3798" class="ember-view reader-text-block__paragraph">The key to getting comfortable with AI is education &ndash; and that means investing time in the tools. Take an active interest in what AI is, what it can do, and how it applies to your world.</p>
<p id="ember3799" class="ember-view reader-text-block__paragraph">For organisations (especially the ones we work with) deploying AI appropriately means having a clear purpose. You need to know your objectives, identify the right use cases, and define how you&rsquo;ll measure success. Without that, adopting AI risks being directionless and ineffective.</p>
<h2 id="ember3800" class="ember-view reader-text-block__heading-2">For you and the team at Covecta, what does &lsquo;AI safety&rsquo; look like in practice?</h2>
<p id="ember3801" class="ember-view reader-text-block__paragraph">Every AI vendor has a responsibility to ensure safe and secure deployment&hellip; from addressing social bias to protecting confidential data. That&rsquo;s non-negotiable.</p>
<p id="ember3802" class="ember-view reader-text-block__paragraph">But we also have to be mindful of how regulation impacts innovation. In the US, looser regulation and a large single market have created the conditions for huge tech companies to thrive. In contrast, Europe&rsquo;s more stringent approach (including the EU AI Act) comes with important safeguards, but also risks slowing growth and competitiveness.</p>
<p id="ember3803" class="ember-view reader-text-block__paragraph">Ultimately, it&rsquo;s about striking the right balance. Strong governance and global responsibility are essential, but so is ensuring that regulation doesn&rsquo;t stifle progress.</p>
<h2 id="ember3804" class="ember-view reader-text-block__heading-2">What have you found to be the biggest challenge when bringing your product to market at scale?</h2>
<p id="ember3805" class="ember-view reader-text-block__paragraph">Our biggest challenge &ndash; and it&rsquo;s an ongoing one &ndash; is scaling the product while maintaining impact and quality.</p>
<p id="ember3806" class="ember-view reader-text-block__paragraph">As we work with more customers and prospects, the volume and complexity of product requirements increase. A key focus will be to ensure we&rsquo;re prioritising the features that will deliver the greatest value to users.</p>
<p id="ember3807" class="ember-view reader-text-block__paragraph">At the same time, we&rsquo;re building an engineering engine that can consistently ship high-quality AI capabilities at scale. That&rsquo;s not a one-off effort. It requires continuous delivery, reliability, and a sharp focus on value. If we&rsquo;re not delivering meaningful impact, organisations will look elsewhere.</p>
<h2 id="ember3809" class="ember-view reader-text-block__heading-2">What kind of team are you building at Covecta, and what qualities or roles are you looking for as you grow?</h2>
<p id="ember3810" class="ember-view reader-text-block__paragraph">We&rsquo;re a lean team by design. In the era of AI, you don&rsquo;t need bloated teams&hellip; you need people with the right expertise and mindset.</p>
<p id="ember3811" class="ember-view reader-text-block__paragraph">We&rsquo;re looking for individuals with deep domain knowledge in either AI or financial services. If you have both, we <em>definitely</em> want to talk.</p>
<p id="ember3812" class="ember-view reader-text-block__paragraph">We value people who can handle complexity and ambiguity, and who are motivated to help reshape the operating model of one of the world&rsquo;s largest industries. There&rsquo;s a new agentic layer emerging in the tech stack &ndash; and joining Covecta means being at the forefront of building that.</p>
<p id="ember3813" class="ember-view reader-text-block__paragraph">We look for curiosity, drive, and people who take real professional pride in their work. Not just in front of the team, but behind the scenes too.</p>
<p id="ember3814" class="ember-view reader-text-block__paragraph">I&rsquo;m excited to share that we&rsquo;re now hiring across the business. Our immediate focus is growing the product and engineering team &ndash; from DevOps and full-stack developers to AI/ML engineers. We&rsquo;re also expanding commercially. But above all, we&rsquo;re focused on shipping high-quality products at scale, and we want people who are excited to help make that happen.</p>
<h2 id="ember3815" class="ember-view reader-text-block__heading-2">Tell us more about the AI engineering role in particular!</h2>
<p id="ember3816" class="ember-view reader-text-block__paragraph">As we grow, our core focus remains on building autonomous, specialised AI agents. Getting that right is critical to Covecta&rsquo;s success.</p>
<p id="ember3817" class="ember-view reader-text-block__paragraph">We're developing a highly verticalised solution for financial services, which means understanding customer workflows deeply and delivering outputs with real relevance and context.</p>
<p id="ember3818" class="ember-view reader-text-block__paragraph">Our AI engineering capability will play a vital role in accelerating product maturity and our long-term scale. We're looking for someone with hands-on experience in natural language processing, large language models, and ideally some MLOps exposure &ndash; you&rsquo;ll be designing, developing, and deploying high-quality AI/ML capabilities, all while ensuring ethical and responsible use, and establishing best practices within the organisation.</p>
<p id="ember3819" class="ember-view reader-text-block__paragraph">This is a fantastic chance to shape the agentic layer of a new tech stack in one of the world&rsquo;s most complex and valuable industries. We're looking for someone excited by hard problems, ideally with experience in a mature organisation, who wants to help build foundational AI infrastructure that defines our technical direction.</p>
<p id="ember3820" class="ember-view reader-text-block__paragraph">We move quickly, and need someone who thrives in that kind of environment. Expect fast iterations, real ownership, and the opportunity to make a tangible impact from day one.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/7aa0ae56-5991-4131-b957-7d46314f0e33" alt="" width="600" height="369"></p>
<h2 id="ember3822" class="ember-view reader-text-block__heading-2">In terms of AI trends, what&rsquo;s genuinely exciting to you right now?</h2>
<p id="ember3823" class="ember-view reader-text-block__paragraph">What&rsquo;s exciting right now is that enterprise AI is moving beyond simple, everyday tasks and being applied to solve complex workflows, particularly in regulated industries like financial services.</p>
<p id="ember3824" class="ember-view reader-text-block__paragraph">One major shift we&rsquo;re seeing is a move from human-in-the-loop systems to fully agentic solutions. In this model, humans aren&rsquo;t completing tasks &ndash; they&rsquo;re overseeing a team of AI agents, stepping into a managerial or supervisory role. That&rsquo;s a significant change in how we think about work.</p>
<p id="ember3825" class="ember-view reader-text-block__paragraph">What stands out is how quickly financial services is moving in this direction. It&rsquo;s a sector many expected to be slow to adopt AI, but in reality, the scale and cost pressure are driving urgency. As one of the world&rsquo;s largest industries, the ripple effects of this transformation will be felt widely &ndash; and that&rsquo;s where it gets really interesting.</p>
<div class="reader-image-block reader-image-block--full-width">
<h2 id="ember3827" class="ember-view reader-text-block__heading-2">You're obviously very busy &ndash;&nbsp;how do you decompress?</h2>
<p id="ember3828" class="ember-view reader-text-block__paragraph">For me, decompression comes from working with people I genuinely enjoy spending time with. The hours are long and the work is intense, but being part of a founding team means we&rsquo;ve chosen to go on this journey together &ndash; and there&rsquo;s real trust, respect, and a shared sense of purpose. That makes a huge difference.</p>
<p id="ember3829" class="ember-view reader-text-block__paragraph">Outside of work, I&rsquo;ve got a toddler at home, which definitely helps keep things in perspective. He makes sure I stay present &ndash; whether I want to or not! And I&rsquo;m lucky to have a very understanding wife who plays a big part in making this all possible.</p>
<p id="ember3830" class="ember-view reader-text-block__paragraph">We&rsquo;re social beings at heart. This industry is built on relationships, and we try to enjoy the ride. Not just work hard, but have a good time doing it.</p>
<h2 id="ember3831" class="ember-view reader-text-block__heading-2">If you weren't working on Covecta, are there any other problems that you&rsquo;d want to solve with AI?</h2>
<p id="ember3832" class="ember-view reader-text-block__paragraph">One of the more frustrating parts of building Covecta isn&rsquo;t the product, it&rsquo;s everything around it. The admin, the red tape, the operational overhead of starting and running a business: payroll, pensions, VAT, banking, budgeting&hellip; the list goes on.</p>
<p id="ember3833" class="ember-view reader-text-block__paragraph">None of it helps you win business, but you can&rsquo;t operate without it. So if I weren&rsquo;t working on Covecta, I&rsquo;d seriously consider building a founder-focused AI assistant&hellip; something that kicks in the moment you incorporate on Companies House, with a chain of agents to guide and manage all those time-consuming tasks.</p>
<p id="ember3834" class="ember-view reader-text-block__paragraph">There are around 6 million SMEs in the UK, and plenty of repeat founders juggling multiple ventures. This kind of burden probably eats up 20&ndash;30% of my time &ndash; so maybe there&rsquo;s a business there. Who knows? Let&rsquo;s get an NDA signed!</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p id="ember3836" class="ember-view reader-text-block__paragraph"><strong>Want to meet 50+ more innovative AI organisations and technical leaders? Our 'Faces of AI 2025' report is available to <a class="EaWzLdfjwgloMRCqeXHrsnLLcqdpxKtzA " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link="">download for free now</a>.</strong></p>
<p id="ember3837" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, <a class="EaWzLdfjwgloMRCqeXHrsnLLcqdpxKtzA " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link="">let's talk.</a></strong></p>
</div>

With a mission to unlock scalable growth in one of the world’s most complex industries, Covecta is building autonomous AI agents tailored for financial services.

“Curiosity, Drive, and Professional Pride” – Scott Wilson on What it Takes to Build Agentic AI for Financial Services

<p dir="ltr">When it comes to AI, the word &ldquo;safety&rdquo; gets thrown around a lot.&nbsp;</p>
<p dir="ltr">Policymakers reference it when drafting new regulations. Tech companies invoke it when launching products. And in headlines, it&rsquo;s often tied to fears of misuse or unintended consequences.</p>
<p dir="ltr">But what does AI safety really mean in practice? Is it about compliance, trust, or simply making sure systems don&rsquo;t break?</p>
<p dir="ltr">We asked founders from across the Faces of AI series to share their perspectives. From healthcare and finance to self-driving cars and simulation technology, here&rsquo;s how they&rsquo;re putting AI safety into action in their own work.</p>
<h2 dir="ltr">Roshan Tamil Sellvan, Advisory AI</h2>
<p dir="ltr">For Roshan, operating in the finance sector leaves no room for error.</p>
<blockquote>
<p dir="ltr"><em>In finance, responsibility starts with building safeguards into the architecture itself. We train our AI to filter inappropriate language, check outputs against FCA regulatory frameworks, and use multi-model verification pipelines to ensure accuracy and compliance. If a report doesn&rsquo;t meet the threshold, it gets rewritten. These layers build trust in the system.</em></p>
</blockquote>
<p dir="ltr">By embedding checks and balances into every step, Advisory AI aims to make compliance a structural feature rather than an afterthought.</p>
<h2 dir="ltr">Eduardo Candela, Maihem</h2>
<p dir="ltr">Eduardo&rsquo;s background in self-driving cars shaped his view of safety as something more nuanced than &ldquo;risk-free.&rdquo;</p>
<blockquote>
<p dir="ltr"><em>Safety is about performance under constraints. In self-driving car simulations, the &lsquo;safest&rsquo; vehicle was the one that parked and never moved &ndash; but that&rsquo;s useless. The question is: how do we achieve goals without crossing boundaries? The challenge is defining those limits and keeping users in control.</em></p>
</blockquote>
<p dir="ltr">In other words, safety isn&rsquo;t about eliminating all risk. It&rsquo;s about making trade-offs explicit and manageable.</p>
<h2 dir="ltr">George Hancock, Octaipipe</h2>
<p dir="ltr">At Octaipipe, the emphasis is on trustworthiness.</p>
<blockquote>
<p dir="ltr"><em>AI safety is broad &ndash; it means different things to practitioners, users, or policymakers. For us, it&rsquo;s about building explainable and trustworthy systems. We&rsquo;ve developed frameworks around transparency, interpretability, and user confidence, and carried those into real-world projects like our work with P&amp;G.</em></p>
</blockquote>
<p dir="ltr">Clear principles, George notes, are key to building systems that people can actually rely on.</p>
<h2 dir="ltr">George Parry, Emma</h2>
<p dir="ltr">Operating in healthcare adds its own layer of responsibility.</p>
<blockquote>
<p dir="ltr"><em>For us, AI safety means clear guardrails and always keeping a human in the loop. Emma makes outputs transparent &ndash; you can see the exact sources behind a recommendation &ndash; but final decisions rest with trained professionals. In health and social care, safe AI means combining machine processing power with human empathy and judgment.</em></p>
</blockquote>
<p dir="ltr">For Emma, AI safety is about pairing machine efficiency with human empathy and judgment.</p>
<h2 dir="ltr">Eric Marcuson, ClinBI</h2>
<p dir="ltr">Eric sees safety as starting from customer needs.</p>
<blockquote>
<p dir="ltr"><em>AI safety starts with deferring to the customer. Legal frameworks set the boundaries, but beyond that we respect individual preferences around data. Guardrails aren&rsquo;t a barrier; they create space for thoughtful innovation. If you build with care and intent, safety and progress can align.</em></p>
</blockquote>
<p dir="ltr">By putting user intent first, ClinBI ensures safety doesn&rsquo;t slow creativity &ndash; it enables it.</p>
<h2 dir="ltr">Scott Wilson, Covecta</h2>
<p dir="ltr">Scott points to the policy landscape shaping how safety is defined.</p>
<blockquote>
<p dir="ltr"><em>Vendors have a responsibility to ensure safe deployment &ndash; from bias to data protection. But regulation has to strike the right balance. Europe&rsquo;s stringent approach offers safeguards but risks slowing innovation. Governance matters, but so does competitiveness.</em></p>
</blockquote>
<h2 dir="ltr">Patrick Sharpe, Artificial Societies</h2>
<p dir="ltr">Patrick frames safety around strict data boundaries and scalable moderation.</p>
<blockquote>
<p dir="ltr"><em>Safety for us means strict data use &ndash; only public content, never private &ndash; and clear moderation guardrails. Our system uses AI to assess audience requests, blocking harmful simulations before they can be created. It&rsquo;s how we keep innovation responsible and scalable.</em></p>
<p dir="ltr">&nbsp;</p>
</blockquote>
<hr>
<h2 dir="ltr">So, What Does It All Add Up To?</h2>
<p dir="ltr">Across industries, AI safety doesn&rsquo;t have a single definition. For some founders, it&rsquo;s about compliance and regulation. For others, it&rsquo;s about explainability, user control, or ethical data use.</p>
<p dir="ltr">But the common thread is clear: AI safety is about building systems that can be trusted by regulators, businesses, and the people who use them.</p>
<p dir="ltr">As George Parry of Emma puts it: &ldquo;With any new technology comes new risks. The key is introducing it with a clear-eyed view of both the known and unknown.&rdquo;</p>
<p dir="ltr">AI safety, then, isn&rsquo;t about playing it safe. It&rsquo;s about innovating responsibly &ndash; and making accountability part of the design from day one.</p>

What does AI safety really mean in practice? We asked founders from across the Faces of AI series to share their perspectives.

What Does ‘AI Safety’ ACTUALLY Mean? Founders Weigh In.

<h2 dir="ltr">At ClinBI, founders Eric Marcuson and Mounir Atassi have identified a simple yet profound truth.</h2>
<p dir="ltr">Behind every growing medical practice is a team grappling with too much uncertainty and limited insight to act with confidence.&nbsp;</p>
<p dir="ltr">Their solution is an AI-powered operational partner that helps navigate complexity and supports smarter, informed decision-making.</p>
<p dir="ltr">But beyond the technology, ClinBI is a people-first startup seeking builders ready to join a journey of growth and impact. We sat down with Eric to discuss what it takes to scale from scratch &ndash; and why honesty and authenticity is key to attracting and retaining new hires with a true startup mindset.&nbsp;</p>
<h2 dir="ltr">What specific problem is ClinBI solving, and why does it matter now?</h2>
<p dir="ltr">We started with a simple observation: our customers are small business owners first, and medical clinic practitioners second. And they want to make informed business decisions.</p>
<p dir="ltr">Many have grown their practices from a single site to a regional presence. They&rsquo;re ambitious, capable entrepreneurs &ndash; but like all founders, they carry a quiet burden of uncertainty.</p>
<p dir="ltr">There&rsquo;s never enough time in the day. And in the back of their minds are questions like: Am I making the right decision? How can I de-risk this? How can I move faster, with more confidence?</p>
<p dir="ltr">That&rsquo;s what we&rsquo;re here for.</p>
<p dir="ltr">We&rsquo;re building an operational business partner that understands the clinic as deeply as its founder does. Maybe more. Something that feels like a coach, a confidant, and a guide.</p>
<p dir="ltr">At its core, we&rsquo;re addressing a very human need: clarity. And we&rsquo;re doing it in a way that&rsquo;s fast, intelligent, and grounded in financial and operational analysis, so our customers can make better decisions and make them faster.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">How did the idea come about? Give us the origin story.</h2>
<p dir="ltr">My co-founder, Mounir, is a dentist. Like me, he left his first profession and stepped into the big wide world of business.</p>
<p dir="ltr">Independently, we both discovered the same thing: many firms aren&rsquo;t being run as well as they could be. But it doesn&rsquo;t take much to turn them around. There&rsquo;s a lot of low-hanging fruit &ndash; simple changes that can make a big difference.</p>
<p dir="ltr">Most SME and mid-market clinic owners don&rsquo;t have business degrees or deep strategy experience. They&rsquo;ve built their practices from the ground up, often without exposure to the kinds of tools and frameworks that could really help them scale.</p>
<p dir="ltr">Not every technique from the corporate playbook applies, but some do. And if we can translate those ideas into something digestible and actionable, we can tap into real impact at scale.</p>
<p dir="ltr">So our origin story is really a convergence. Two different industries, one shared insight: small businesses everywhere could thrive if they had the right business support, delivered in a way they could actually use.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">There&rsquo;s a lot of uncertainty, even fear, in the wider population when it comes to AI. What are some of the most common misconceptions you hear?</h2>
<p dir="ltr">I was having dinner with a good friend recently and he said to me, &ldquo;What did AI ever do for us?&rdquo;</p>
<p dir="ltr">That question really stuck with me. Do you respond with stats? With use cases? But what stood out wasn&rsquo;t the specifics, it was that AI hadn&rsquo;t yet connected with him personally.</p>
<p dir="ltr">I think that&rsquo;s true for a lot of people. There&rsquo;s still an us-versus-them mindset around AI. For me, it's part of my daily life. My relationship with Google has changed. I now use AI tools to work, learn, think differently, and reduce friction &ndash; and I like the idea that it&rsquo;s working for me.&nbsp;</p>
<p dir="ltr">So the question people are really asking is: What will AI do for me?</p>
<p dir="ltr">And that question brings up a lot &ndash; your past experiences with technology, whether you find change empowering or threatening, whether your relationship with tech has felt adversarial or enabling. One of the biggest barriers is that AI still feels like a black box.&nbsp;</p>
<p dir="ltr">But we saw the same thing with electricity and automobiles. People didn&rsquo;t understand how they worked at first, either. Sure, AI will disrupt the way people work for better and worse&hellip; but that&rsquo;s the nature of progress. When cars came along, we needed fewer blacksmiths making horseshoes &ndash; but more mechanics.</p>
<p dir="ltr">Everyone&rsquo;s relationship with AI will look different. For some, it&rsquo;ll help them survive today; for others, it&rsquo;ll unlock their future ambitions. It fits all over Maslow&rsquo;s hierarchy. But there&rsquo;s no one-size-fits-all answer.</p>
<p dir="ltr">So while this isn&rsquo;t a specific problem ClinBI is solving, I do think it&rsquo;s something we, as founders building with AI, have the responsibility and opportunity to shape. How we present it, how we build with it, how we bring people into the conversation &ndash; all of that influences whether it feels empowering or alienating.</p>
<p><strong><br><br></strong></p>
<h2 dir="ltr">&ldquo;AI safety&rdquo; can mean very different things depending on who you're speaking to. For you, what does AI safety actually look like in practice?</h2>
<p dir="ltr">There are really two schools of thought here. For us, it starts with deferring to the customer.</p>
<p dir="ltr">We operate in a quasi-medical space, so there are strict legal boundaries around what we can and can&rsquo;t do. Those are non-negotiable.</p>
<p dir="ltr">But beyond that, there's the creative side of AI &ndash; and that&rsquo;s where it gets personal. Personally, I'm pretty data-open. I'm not too concerned about who has access to my data. But not everyone feels the same and we have to respect that, whether it's a temporary discomfort or a permanent preference.</p>
<p dir="ltr">So when we build, the first question we ask is: are we acting on the customer's behalf?</p>
<p dir="ltr">Ultimately, we want to be a force for good. If you're not, your shelf life tends to be short. We follow best practices in data security, adhere to all relevant legal frameworks, and build with care. Fortunately, a lot of modern tools &ndash; including low-code platforms and digital service providers &ndash; are secure by design, because they have to be.</p>
<p dir="ltr">We don&rsquo;t see safety as a barrier. Guardrails create space for thoughtful innovation. And if you start from a place of positive intent, you&rsquo;ll naturally align with ethical, legal, and regulatory standards.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/19288a04-a2a0-4028-b158-f293d4df78ef" alt="" width="600" height="401"></p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">What has been the biggest challenge in bringing ClinBI to market at scale?</h2>
<p dir="ltr">For most founders, one of the biggest challenges is figuring out what customers actually want.</p>
<p dir="ltr">There are so many projects building toward open-ended outcomes. But the real task is delivering clear, high-quality value in a way customers can appreciate before day one. If you can do that, a lot of other things start to fall into place.</p>
<p dir="ltr">But product&ndash;market fit isn&rsquo;t something you check off and move on from. It&rsquo;s ongoing. Product&ndash;channel fit evolves. Customer value shifts. All of it changes over time, and you have to be aware of this.</p>
<p dir="ltr">We wrestle with that just like everyone else.</p>
<p dir="ltr">The other big challenge is people. You're working with humans&hellip; and humans are complex. Whether it&rsquo;s your team or your customers, understanding how people think, communicate, and collaborate is critical. Interpersonal dynamics matter. As does maintaining a high speed of iteration, learning, and improving. That means always talking to the customer, and those around them.</p>
<p dir="ltr">So those are the two big ones for us: staying close to evolving customer value, and building alignment to a shared vision. We're figuring it out like everyone else.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">What are you looking for in future hires?</h2>
<p dir="ltr">Our team is super small. Probably smaller than you&rsquo;d expect! And while some see that as a disadvantage, we see it as an opportunity.</p>
<p dir="ltr">Once you hit 16&ndash;20 people, you start to face real managerial and structural challenges. We&rsquo;re well below that threshold, and intentionally so.</p>
<p dir="ltr">For the right person, that&rsquo;s attractive. If you&rsquo;re looking for stability (a corporate role with a ticket-based management system, mortgage covered, and minimal risk) we&rsquo;re probably not for you. And that&rsquo;s okay. But if you want to work with experienced founders who&rsquo;ve built things before, who understand the customer, and who are aiming to build something that scales &ndash; that&rsquo;s our niche.</p>
<p dir="ltr">We&rsquo;re not just selling to customers; we&rsquo;re also &ldquo;selling&rdquo; to potential teammates. If someone&rsquo;s going to give us years of their life, we owe them more than just a salary. They want to be heard. They want equity, upside, creativity, fun. They want to build.</p>
<p dir="ltr">That&rsquo;s who we&rsquo;re looking for. Builders who want to come on a journey with a high probability of success, a solid foundation, and leaders who listen.</p>
<p dir="ltr">We&rsquo;re not a top-down org. We're looking for experienced people with diverse skillsets &ndash; that diversity fuels creativity, encourages alternative approaches to problem-solving, and drives high innovation potential. It's a key part of our company value. And while that means we&rsquo;re not for everyone, we&rsquo;re very clear about what we are, and that authenticity helps us find the right people.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/d398f5f0-65c9-4c95-9332-93a2ebb6f735" alt="" width="600" height="449"></p>
<h2 dir="ltr">You&rsquo;re obviously incredibly busy. How do you decompress outside of work?</h2>
<p dir="ltr">First and foremost, you have to nourish yourself by eating well. That means smart, intentional choices that support your body and mind.</p>
<p dir="ltr">You also need people around you whose opinions you respect. I&rsquo;m incredibly lucky to be married to someone like that. She&rsquo;s brilliant, analytical, and strategic &ndash; and also a very different personality to mine, but we understand each other&rsquo;s languages completely.&nbsp;</p>
<p dir="ltr">Kids are great for perspective. They force you to decompress, whether you want to or not!</p>
<p dir="ltr">There was a time when I did a lot of extreme sports &mdash; and part of the draw was that it made it impossible to think about work. That total focus was a kind of freedom.</p>
<p dir="ltr">Now, I run. I read. I average two books a week, and that&rsquo;s hugely important to me. It&rsquo;s how I reset and reframe.</p>
<h2><strong>&nbsp;</strong></h2>
<h2 dir="ltr">Finally, if you weren't working on ClinBI, what other problems would you be trying to solve with AI?</h2>
<p dir="ltr">It might sound a bit anti-Founder, but in my former life, I made furniture. You&rsquo;re working with your hands, creating something tangible. You control the process. The conflict is between your vision, tools, and the materials at hand. I&rsquo;d probably spend some time doing that again.</p>
<p dir="ltr">But if you&rsquo;re talking big-picture &ndash; the kind of global problem I&rsquo;d want to work on &ndash; I think it would be space exploration. There&rsquo;s something profound about the idea of exploration.</p>
<p dir="ltr">Earth is, in some ways, our practice run. And if we can carry forward the right lessons (assuming we can capture them, and implement them) there&rsquo;s an opportunity to build something entirely new. To have a truly new opportunity is rare, and outer space is the place that offers it!</p>
<p>&nbsp;</p>

ClinBI is an AI-powered operational partner that helps navigate complexity and supports smarter, informed decision-making.

“Clarity Is the Human Need We’re Here to Solve” Eric Marcuson on Empowering Time-Strapped Entrepreneurs

<h3 id="ember1608" class="ember-view reader-text-block__heading-3">Plenty of startups talk about vision. But at Emma, George Parry and Charles Cross have been putting in the work to turn that vision into results.</h3>
<p id="ember1609" class="ember-view reader-text-block__paragraph">In Part 2 of our interview, the co-founders dig into the practical realities of building AI for health and social care &ndash; from naming a product that people trust, to building in public, solving deep technical challenges, and getting the right people on board.</p>
<hr>
<h2 id="ember1610" class="ember-view reader-text-block__heading-2">What has been the biggest challenge in bringing an AI product like yours to market?</h2>
<p id="ember1611" class="ember-view reader-text-block__paragraph"><strong>GEORGE:</strong> I think the biggest challenge we&rsquo;ve tackled has been engineering the <strong>deep tech at the heart of Emma</strong>. Specifically, how you build a system where any user can ask any question, about any part of their data, at any time, and get an output in whatever format they need. That&rsquo;s been our hardest technical problem, but also the thing driving our growth.</p>
<p id="ember1612" class="ember-view reader-text-block__paragraph">Another major challenge we&rsquo;ve come up against is the issue of <strong>interoperability in health and social care</strong>. A lot of technology companies treat patient data as their moat &ndash; even though it&rsquo;s not their data to own, it belongs to the end user. But technology companies ring-fence it because it protects their business, which creates huge barriers to delivering best in class care.</p>
<p id="ember1613" class="ember-view reader-text-block__paragraph">That was a real blocker for us 12 months ago, but it&rsquo;s something we&rsquo;ve worked through. And as we move forward, Emma will be the opposite of that: an <strong>open platform anyone can connect to and from</strong>. With AI, you don&rsquo;t need rigid connections in the way you did before. Data transfer can be far more flexible, and if you structure your business the right way, you don&rsquo;t need to rely on controlling patient data as your competitive advantage.</p>
<p id="ember1614" class="ember-view reader-text-block__paragraph">And on a similar note, another challenge (but one we&rsquo;re proud to be solving) is around <strong>building flexibility into the product itself</strong>. For too long, a handful of tech companies have effectively dictated how care companies operate through rigid tooling. That needs to change.&nbsp; What we&rsquo;ve worked hard to do is create a platform that&rsquo;s flexible enough for a small local care team or a national provider to configure it in a way that works for them.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/25b9b702-5e09-498e-a57f-c247e0e66614" alt="" width="600" height="399"></p>
<p id="ember1616" class="ember-view reader-text-block__paragraph"><strong>CHARLES:</strong> One of the biggest challenges has been <strong>bridging the gap</strong> between initial excitement around AI and real-world impact. There's a clear distinction between B2C and B2B AI &ndash; with B2C tools like ChatGPT, users expect something plug-and-play. But in a regulated, human-centred sector like care, that approach doesn&rsquo;t work.</p>
<p id="ember1617" class="ember-view reader-text-block__paragraph">Our focus has always been on making AI safe, ethical, and genuinely useful in context. That&rsquo;s why we built Emma with a partnership model from day one. We work closely with providers to deeply understand their goals, and we feed that directly into the product. Building in public sounds great in theory, but actually doing it means staying open to feedback, iterating fast, and being okay with tough conversations.</p>
<p id="ember1618" class="ember-view reader-text-block__paragraph">Another big challenge has been managing the shift from <em>vision</em> to <em>validation</em>. When we launched, we knew we had a compelling idea. But turning that into a proven, valuable tool takes time, trust, and results. We're proud to now be delivering measurable outcomes for providers and showing how AI, done right, can drive real change in care.</p>
<h2 id="ember1620" class="ember-view reader-text-block__heading-3">Can you share a bit more about what that name &lsquo;Emma&rsquo; represents and what kind of relationship you hope users have with the product?</h2>
<p id="ember1621" class="ember-view reader-text-block__paragraph"><strong>CHARLES: </strong>We thought long and hard about what to call the product. We considered technical names, ones that sounded futuristic&hellip; but none of them really captured what we were trying to build. In the end, we landed on &ldquo;Emma&rdquo; because it felt human, familiar, and supportive.</p>
<p id="ember1622" class="ember-view reader-text-block__paragraph">Emma is designed to feel like someone in your corner &ndash; the colleague you trust, who knows your service inside out and is always there to help. Whether you&rsquo;re a care worker, a manager, or C-suite, Emma should feel like part of your team: reliable, knowledgeable, and easy to work with.</p>
<p id="ember1623" class="ember-view reader-text-block__paragraph">That sense of safety and consistency is something we heard again and again from people delivering care. They didn&rsquo;t want some dashboard or generic system. They wanted something that felt personal; something they could rely on every day. That&rsquo;s what the name Emma represents.</p>
<h2 id="ember1624" class="ember-view reader-text-block__heading-2">How has the talent attraction process been so far for you?</h2>
<p id="ember1625" class="ember-view reader-text-block__paragraph"><strong>GEORGE: </strong>The team is quickly growing at the moment &ndash; it&rsquo;s an exciting time for us!</p>
<p id="ember1626" class="ember-view reader-text-block__paragraph">I&rsquo;ll be honest &ndash; we&rsquo;ve been on a journey with our talent attraction. At first, we tried going it alone and didn&rsquo;t have much success. We then partnered with Generative and it&rsquo;s been a completely different experience. The calibre of candidates they&rsquo;ve brought in has been brilliant. Everyone they&rsquo;ve introduced us to understands the mission we're on, they challenge our thinking in a good way, and there&rsquo;s a real alignment in those conversations.</p>
<p id="ember1627" class="ember-view reader-text-block__paragraph">What&rsquo;s made it work so well is that Generative is a startup too &ndash; so they just <em>get it</em>. They understand how important these early hires are and how quickly things need to move. Working with them has made the whole process so much easier and more effective.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/8694e3c3-afe2-45ad-a997-e3fc50d06a5d" alt="" width="600" height="399"></p>
<h2 id="ember1629" class="ember-view reader-text-block__heading-2">In terms of AI trends, what&rsquo;s exciting to you &ndash; and what do you think is overhyped?</h2>
<p id="ember1630" class="ember-view reader-text-block__paragraph"><strong>GEORGE: </strong>For me, the most exciting trend in AI right now is the development of agents.</p>
<p id="ember1631" class="ember-view reader-text-block__paragraph">At Emma, our product development has involved exploring ideas through R&amp;D &ndash; and often discovering that the underlying models just aren&rsquo;t ready yet. And this is exactly the right space to be: where you&rsquo;ve got the vision and the solution, but the models haven&rsquo;t quite caught up yet.</p>
<p id="ember1632" class="ember-view reader-text-block__paragraph">Agents are a great example. As complexity increases (more tasks, more tools, more agents in the network) the chances of failure or an incorrect output also go up. That&rsquo;s why they haven&rsquo;t been truly viable until now, especially in healthcare where the stakes are high. But with Claude 4, Gemini 2.5, and no doubt OpenAI&rsquo;s next release soon, we&rsquo;re seeing real leaps in capability.</p>
<p id="ember1633" class="ember-view reader-text-block__paragraph">As foundational models get better, agents will shift the fundamental business model &ndash; and I think that&rsquo;s massively exciting. It&rsquo;s not overhyped. It just hasn&rsquo;t been possible until now.</p>
<p id="ember1634" class="ember-view reader-text-block__paragraph">And what&rsquo;s <em>overhyped</em>? Point solutions that inject AI into parts of a workflow without rethinking the bigger picture. You might get a flashy demo and a slight productivity gain, but you&rsquo;re not tapping into what this technology can really do.</p>
<p id="ember1635" class="ember-view reader-text-block__paragraph">And more technically, there&rsquo;s a question around the current scaling approach for training large language models. There's been commentary, like from Hugging Face&rsquo;s CEO, asking how far we can keep scaling these models before we need a different breakthrough entirely.</p>
<p id="ember1636" class="ember-view reader-text-block__paragraph">So far, making them bigger has worked. But I think at some point, someone&rsquo;s going to crack a new method that fundamentally changes how we push intelligence forward.</p>
<h2 id="ember1638" class="ember-view reader-text-block__heading-2">If you weren't working on Emma, what other problems would you be trying to solve with AI?</h2>
<p id="ember1639" class="ember-view reader-text-block__paragraph"><strong>CHARLES:</strong> If I weren&rsquo;t working on Emma, I&rsquo;d still be drawn to social care&hellip; it holds my heart, my soul, and my mind. This sector means everything to me.</p>
<p id="ember1640" class="ember-view reader-text-block__paragraph">I see myself dedicated to it for decades to come. Right now, my focus is 100% on Emma and the impact we can create.</p>
<p id="ember1641" class="ember-view reader-text-block__paragraph">Given the complexity of the system and the scale of the challenges we face here in the UK, that alone is more than enough to keep me up at night!</p>
<p id="ember1642" class="ember-view reader-text-block__paragraph"><strong>GEORGE:</strong> It&rsquo;s an interesting one. Before Emma, I believed that healthcare would be one of the biggest areas impacted by generative AI. And I still do. But I think the place that might actually see the <em>first</em> and most profound impact is education.</p>
<p id="ember1643" class="ember-view reader-text-block__paragraph">It comes down to a similar principle that we&rsquo;ve talked about before: healthcare admin work is limited because people can only do so many hours of knowledge work. Teaching faces the same challenge &ndash; classroom sizes, access to personalised information, and individual support have always been bottlenecks.</p>
<p id="ember1644" class="ember-view reader-text-block__paragraph">When Google came around, it promised democratisation of information. And it delivered, to some extent. But now, generative AI provides PhD-level intelligence in your pocket. It can communicate however you want, is infinitely patient, and creatively adapts. It&rsquo;s bound to fundamentally change access to education.</p>
<p id="ember1645" class="ember-view reader-text-block__paragraph">It&rsquo;s not just about access &ndash; it&rsquo;s about opportunity for learners everywhere. The education system as we know it will need to evolve drastically. For example, kids will have tools like ChatGPT to write essays (and they <em>will</em> use it) so we have to rethink how we assess learning in a way that fits this new reality.</p>
<p id="ember1646" class="ember-view reader-text-block__paragraph">It&rsquo;s similar to what we see in tech hiring. You can&rsquo;t set the same technical challenges as before because people have access to AI that&rsquo;s among the best programmers in the world. The fundamentals of software engineering &ndash; and education in general &ndash; are shifting fast.</p>
<p id="ember1647" class="ember-view reader-text-block__paragraph">If I weren&rsquo;t working on healthcare, I&rsquo;d be deeply focused on education, because the benefits AI can bring there are <em>huge</em> and it&rsquo;s an incredibly exciting space to be in.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/4b840214-dcd0-4adf-8692-72acf5f1b9d2" alt="" width="600" height="399"></p>
<h2 id="ember1649" class="ember-view reader-text-block__heading-2">You&rsquo;re obviously incredibly busy. How do you relax and switch off outside of work?</h2>
<p id="ember1650" class="ember-view reader-text-block__paragraph"><strong>GEORGE:</strong> Yeah, Emma definitely takes up a lot of my time! But outside of work, exercise is a big one for me.</p>
<p id="ember1651" class="ember-view reader-text-block__paragraph">I&rsquo;m really into running. Charles and I are heading out to Dallas later this year to take on a Hyrox, which should be a good challenge.</p>
<p id="ember1652" class="ember-view reader-text-block__paragraph">And catching up with friends! They&rsquo;re doing exciting things too, so it&rsquo;s good to swap ideas and sometimes get fresh perspectives on Emma.</p>
<p id="ember1653" class="ember-view reader-text-block__paragraph"><strong>CHARLES: </strong>Same here &ndash; I find movement and physical training really help me reset. I&rsquo;m a big fan of hot yoga, which I&rsquo;ve been doing for years. They call it moving meditation, and I wouldn&rsquo;t disagree. That, alongside strength training for the Hyrox, keeps me focused.</p>
<p id="ember1654" class="ember-view reader-text-block__paragraph">And then on the more reflective side, I love playing chess. Bit of a nerdy one, but it&rsquo;s a great way to challenge the mind and switch gears from the day-to-day.</p>
<p id="ember1655" class="ember-view reader-text-block__paragraph">I think having that balance, exerting both body and mind, is really important.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p id="ember1657" class="ember-view reader-text-block__paragraph"><strong>Emma is one of the 54 innovative AI organisations featured in our 'Faces of AI 2025' report, which is available to </strong><a class="wsMvqdsCQwHMdXuvCLlSAkmVYButhGSUc " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now</strong></a><strong>.</strong></p>
<p id="ember1658" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="wsMvqdsCQwHMdXuvCLlSAkmVYButhGSUc " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link=""><strong>let's talk.</strong></a></p>

Plenty of startups talk about vision. But at Emma, George Parry and Charles Cross have been putting in the work to turn that vision into results.

“Emma Is More Than a Name” Building Health and Social Care AI To Become a Trusted Colleague

<h3 dir="ltr">Admin is breaking the care system. Emma is using AI to fix it.</h3>
<p dir="ltr">George Parry didn&rsquo;t set out to transform healthcare. But after a chance conversation with his now co-founder, Charles Cross, they saw the potential to fundamentally rethink how the system operates.</p>
<p dir="ltr">Together, they built Emma: aiming to put humans back at the heart of care. We caught up with George and Charles to talk AI safety, care capacity, and why the most powerful systems put humans first.</p>
<hr>
<h2 dir="ltr">What specific problem is Emma solving, and why does it matter now?</h2>
<p dir="ltr"><strong>GEORGE:</strong> Emma is exploring how to tap into the vast amounts of data generated through everyday care delivery and conversation. This helps assessors and office teams work more efficiently, ultimately enabling more time for high-quality, person-centred care.</p>
<p dir="ltr">Traditional processes were designed around the limitation that any given person can only process a certain amount of information in a day. With AI, that constraint disappears. It creates an opportunity to rethink how care businesses operate &ndash; moving from fixed, infrequent assessments (like a six-monthly service user review) to dynamic, real-time updates based on live data.</p>
<p dir="ltr"><strong>CHARLES: </strong>And this problem has never been more urgent. Social care is facing a chronic funding shortfall &ndash; more than &pound;5 billion &ndash; while demand continues to grow. At the same time, many providers are reaching a crisis point: handing back contracts, citing unsustainable fee rates, and struggling to attract or retain staff.</p>
<p dir="ltr">Digital transformation has helped, but it&rsquo;s not enough on its own. Many providers now face a patchwork of disconnected systems without a coherent AI strategy to bring everything together.&nbsp;</p>
<p dir="ltr">We built Emma to reimagine how care businesses operate, helping them become more sustainable for the long term. Unlike sectors like finance that work in binary numbers, care is built on language. People speak, document, and deliver care in natural language. AI finally gives us the tools to understand and act on that at scale.</p>
<p dir="ltr">We&rsquo;re building an AI-first operating system for care. One that uses natural language data to ensure compliance, quality, and outcomes across services. For providers, it means less time on governance and more time focused on delivering a high quality of care.</p>
<p dir="ltr">That&rsquo;s what really matters, and that&rsquo;s the mission Emma is here to support.</p>
<p><img src="https://cdn.sourceflow.co.uk/__gallery/46875b17-b200-4ef5-b579-1a4fed35cf6f" alt="" width="399" height="600"></p>
<h2 dir="ltr">How did the idea come about? What's the origin story?</h2>
<p dir="ltr"><strong>GEORGE:</strong> Emma has quite a natural origin story. My background is in AI and computer vision, and my co-founder Charles runs several Social Care businesses in Essex. We actually met by chance at a dinner &ndash; sat next to each other, started chatting, and I couldn&rsquo;t quite believe some of the processes he was describing. I quickly realised that there was a lot of opportunity for growth,</p>
<p dir="ltr">We started working together by asking a simple question: How can we run the most effective care business possible using technology? So we began building tools specifically for Charles&rsquo; care businesses &ndash; testing them out in the real world, getting feedback from the team, and improving them.</p>
<p dir="ltr">As carers and assessors began using the tools, it became clear we were onto something. What started as internal tooling for one business quickly evolved into a platform with much wider potential. Now, we&rsquo;re partnering with large-scale care organisations across the UK to bring that same transformation to the rest of the sector.</p>
<h2 dir="ltr">Charles, you&rsquo;d worked in healthcare before co-founding Emma. What drew you to the sector, and how did that experience shape the startup journey?</h2>
<p dir="ltr"><strong>CHARLES: </strong>My academic background is in economics, but I&rsquo;ve always had a personal connection to care. We had a family-run home care business in Essex, and many of the people we supported were our own relatives. That experience shaped a lot. I saw how vital good care is, and how much of a difference it makes when it's delivered well.</p>
<p dir="ltr">At the time, I was coming from a finance background, where systems were far more advanced. Social care hadn&rsquo;t digitised yet, and it felt like there was a huge opportunity to modernise things. We grew the business, then acquired another that had been rated &lsquo;Inadequate&rsquo; by the CQC and was facing closure. Within 18 months, we&rsquo;d quadrupled the revenue, brought the service back into compliance, and improved the CQC rating to &lsquo;Good&rsquo;.</p>
<p dir="ltr">That experience &ndash; scaling teams, navigating regulation, and working with local authorities &ndash; gave me a clear view of what the sector really needed. And when I couldn&rsquo;t find the technology I knew would help, we built it ourselves. That&rsquo;s where Emma began.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/97a30a20-6864-4e1b-89eb-84ab456e6786" alt="" width="399" height="600"></p>
<h2 dir="ltr">There&rsquo;s a lot of uncertainty in the wider population when it comes to AI. What are some of the most common myths or misconceptions you hear about AI?</h2>
<p dir="ltr"><strong>GEORGE: </strong>It&rsquo;s a good question. We&rsquo;re quite lucky in that the companies we work with tend to be very forward-thinking in how they approach AI. But one of the biggest misconceptions I come across &ndash; whether it&rsquo;s with new clients or just in the general conversation about AI &ndash; is the idea that you can simply bolt AI onto existing processes and expect transformational results.</p>
<p dir="ltr">People often think it&rsquo;s about adding a bit of AI here or there, like integrating a chatbot or giving staff access to ChatGPT. And while you might see some small benefits from that, you won&rsquo;t unlock the full potential. The real gains (the 5x, 10x improvements in productivity) only come when you fundamentally rethink how a business operates with AI at its core.</p>
<p dir="ltr">It reminds me of what Microsoft&rsquo;s CEO said about the energy transition. It took decades for factories to fully redesign their systems to make the most of electricity. It&rsquo;s going to be the same with AI. These shifts take time and aren&rsquo;t purely about technology.</p>
<p dir="ltr">You could hand someone the best AI tools in the world, but without people management, change management, and a clear explanation of why workflows need to evolve, it won&rsquo;t have the impact you&rsquo;re hoping for.</p>
<p dir="ltr"><strong>CHARLES: </strong>Early on, there were justified concerns about large language models&rsquo; performance. That&rsquo;s improved, and we&rsquo;ve built specific guardrails, including a zero data retention policy, so user data isn&rsquo;t used for training models.</p>
<p dir="ltr">Transparency is key. At Emma, we give humans full visibility into how AI arrives at its answers. It&rsquo;s a design challenge we&rsquo;ve solved by ensuring users can see exactly how AI recommendations are generated.</p>
<h2 dir="ltr">The term &ldquo;AI safety&rdquo; often means different things depending on who you're speaking to. For the team at Emma, what does it actually look like in practice?&nbsp;</h2>
<p dir="ltr"><strong>GEORGE: </strong>For us, AI safety has been built into Emma from day one, and we approach it in two key ways.</p>
<p dir="ltr">The first is putting clear guardrails in place. We design the system so conversations and outputs are always aligned with the specific context we&rsquo;re working in,&nbsp; making sure it operates within safe, appropriate boundaries. That includes controlling who has access to certain information, and taking AI out of the loop entirely for highly sensitive operations.</p>
<p dir="ltr">Most importantly, we always keep a human in the loop. That&rsquo;s fundamental for us. AI is brilliant at processing huge volumes of data and surfacing insights no individual could realistically manage alone. But the final decision should always sit with a trained professional.&nbsp;</p>
<p dir="ltr">And to support that, as Charles mentioned, everything Emma outputs is fully transparent. You can click a &lsquo;see sources&rsquo; button and view exactly which five or six pieces of information the AI pulled from, the reasoning behind the recommendation, and how it arrived at that conclusion.&nbsp;</p>
<p dir="ltr">It means you get the best of both worlds: the data-processing power of a language model, and the intuition, experience, and empathy of a human. That combination is how you create safe, effective AI systems in health and social care.</p>
<p dir="ltr">More broadly, I think it&rsquo;s important to recognise that with any new technology comes new risks. We&rsquo;ve gone from paper to digital to AI &ndash; and each of those transitions brought different challenges. The key is that the people responsible for introducing these technologies do so with a clear-eyed view of both the known and unknown risks, and actively manage them.</p>
<p dir="ltr">Yes, adopting AI in healthcare comes with new processes to learn. But resisting it could mean missing out on far better outcomes for the people who matter most: those receiving care. Embracing it opens the door to faster, more accurate, and more person-centred support.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/75990492-55e6-49b6-b90e-a14d25221508" alt="" width="600" height="399"></p>
<p dir="ltr"><strong>CHARLES:</strong>&nbsp; Alongside our work in transparency and visibility, we also worked closely with the Oxford project in partnership with Oxford University on ethical AI in social care, which brought together providers, technologists, and people with lived experience to shape best practice. The bottom line is: care is a regulated, human-driven sector &ndash; so any AI in this space has to be transparent, accountable, and co-produced with the people it&rsquo;s designed to support.</p>
<p dir="ltr">Unlike some European models of social care, which are built around self-managing teams with minimal infrastructure, the UK&rsquo;s care system is more regulated and structured. That&rsquo;s why Emma is designed specifically to support compliance and safe delivery within the UK framework.</p>
<p dir="ltr">We work in close partnership with customers, looking at their workflows, roles, and organisational policies to train the AI in context. It means safer processes, more consistent decision-making, and clearer governance &ndash; all of which are essential for building trust in AI systems that support real people.</p>
<hr>
<p><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p id="ember1657" class="ember-view reader-text-block__paragraph"><strong>Emma is one of the 54 innovative AI organisations featured in our 'Faces of AI 2025' report, which is available to </strong><a class="wsMvqdsCQwHMdXuvCLlSAkmVYButhGSUc " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now</strong></a><strong>.</strong></p>
<p id="ember1658" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="wsMvqdsCQwHMdXuvCLlSAkmVYButhGSUc " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link=""><strong>let's talk.</strong></a></p>

Admin is breaking the care system. Emma is using AI to fix it.

The Hidden Cost of Care: Inside Emma’s Mission to Fix Healthcare Admin

<p dir="ltr">AI is everywhere. In the news, in the tools we use, and in the strategy decks of every ambitious startup.&nbsp;</p>
<p dir="ltr">But while adoption is rising, so is confusion.</p>
<p dir="ltr">We asked founders from across the Faces of AI series to weigh in on the biggest myths they&rsquo;re still encountering in conversations with clients, customers, and teams. Here&rsquo;s what they told us.</p>
<hr>
<h2 dir="ltr">1) &ldquo;You can bolt AI onto existing processes and expect transformational results&rdquo;</h2>
<p dir="ltr">AI isn&rsquo;t a magical solution to all business problems.&nbsp;</p>
<p dir="ltr">If you&rsquo;re already in the space, you&rsquo;ll know that. But as George Parry, CTO at Emma, points out, the idea that AI is a guaranteed golden ticket to perfect workflows still crops up time and time again:</p>
<h5 dir="ltr"><em>People often think it&rsquo;s about adding a chatbot or giving staff access to ChatGPT. And while that might help a little, the real gains only come when you rethink how a business operates with AI at its core.</em></h5>
<h5 dir="ltr"><em>You could hand someone the best AI tools in the world&hellip; but without people management, change management, and a clear explanation of why workflows need to evolve, it won&rsquo;t have the impact you&rsquo;re hoping for.</em></h5>
<p>In other words, transformation doesn&rsquo;t come from tooling alone. It comes from redesigning the way people and processes interact with those tools.</p>
<hr>
<p dir="ltr">This challenge becomes even more complex when you look under the hood.&nbsp;</p>
<p dir="ltr">Eduardo Mandela, co-founder of Maihem, sees the same disconnect but from a deeply technical perspective.</p>
<h5 dir="ltr"><em>We see it across the board &ndash; people are very aware of AI&rsquo;s power, but there&rsquo;s still a lot of scepticism around it.&nbsp;</em></h5>
<h5 dir="ltr"><em>One of the key things many people don&rsquo;t realise is that these new models are probabilistic. You can give them the same input twice and get two completely different outputs.</em></h5>
<p dir="ltr">That unpredictability doesn&rsquo;t just surprise users, it undermines their confidence in the tools entirely. Hallucinations (or confidently wrong outputs) are consistently flagged by founders as to be one of the biggest hurdles to meaningful adoption right now.&nbsp;</p>
<p dir="ltr">When trust is lost, engagement drops fast. Eduardo continues:&nbsp;</p>
<h5><em>There&rsquo;s a real gap between what people think AI should be capable of and how these technologies actually work. They&rsquo;re still not perfect.</em></h5>
<hr>
<h2 dir="ltr">2) &ldquo;AI = ChatGPT&rdquo;</h2>
<p dir="ltr">Generative AI might have put artificial intelligence firmly into the public consciousness, but the field is far broader and older than many people realise. As Ivan Scattergood, CTO of OctaiPipe, puts it:&nbsp;</p>
<h5 dir="ltr"><em>To people outside the space, AI often just means &lsquo;ChatGPT&rsquo; now. But I studied neural networks back in the &rsquo;90s. The maths hasn&rsquo;t changed &ndash; what&rsquo;s changed is data and computation.</em></h5>
<p dir="ltr">The synonymous use of "AI" and "ChatGPT" reflects just how narrow public understanding still is. The overwhelming focus on chatbot functions has obscured AI&rsquo;s wider applications &ndash; in optimisation, automation, forecasting, recommendation systems, and more.&nbsp;</p>
<p dir="ltr">As adoption accelerates, education needs to catch up. The hype can obscure the real work &ndash; and it&rsquo;s changed how startups present themselves, even when the underlying tech hasn&rsquo;t.</p>
<h5 dir="ltr"><em>We used to avoid saying &lsquo;AI&rsquo; at all. We&rsquo;d say ML, because that&rsquo;s what we were actually doing. We even had a joke: if you&rsquo;re talking to investors, it&rsquo;s AI. If you&rsquo;re hiring, it&rsquo;s ML. And when you&rsquo;re building the thing, it&rsquo;s logistic regression.</em></h5>
<p dir="ltr">In reality, most startups don&rsquo;t need the flashiest, most complex models. They need ones that are accurate, stable, and fit for purpose.</p>
<p dir="ltr">That&rsquo;s something Katya Lait, founder of nettle, sees regularly in conversations with customers:</p>
<h5><em>Customers get really excited and ask,&nbsp; &ldquo;Can it do this? Can it do that?&rdquo;&nbsp; We&rsquo;ll get a list of 10&ndash;20 things they want nettle to do. It&rsquo;s great and exciting, but building the kind of features they want takes time, and we have to temper expectations a little bit in the short term.</em></h5>
<p dir="ltr">For founders, managing expectations is now part of the job &ndash; especially when the hype outpaces the reality of what AI can (and should) do.</p>
<hr>
<h2>3) &ldquo;It&rsquo;s taking over the world&hellip; and our jobs&rdquo;</h2>
<p dir="ltr">Fear is still one of the biggest blockers to adoption &ndash; and not just among technophobes. For many users, it&rsquo;s not the capabilities of AI that concern them most, but the uncertainty around how it works (and what it might be doing behind the scenes.)</p>
<p dir="ltr">Katya Lait regularly sees scepticism surface in client conversations:</p>
<h5><em>They may misunderstand what's happening, so they'll think that we&rsquo;re reading all of their data, all of their personal information. They don&rsquo;t trust the system and want us to list every single source we use.</em></h5>
<p>That underlying mistrust isn&rsquo;t always rooted in the tech itself. Often, it&rsquo;s the result of a lack of transparency, or simply a fear of being left behind. George Hancock, CEO at OctaPipe, notes a familiar sentiment:</p>
<h5 dir="ltr"><em>We often hear hesitancy to the tune of "I don&rsquo;t know it, I don&rsquo;t trust it, I don&rsquo;t want to use it."</em></h5>
<p dir="ltr">And in some cases, those fears are generational. Roshan Tamil Sellvan, co-founder at AdvisoryAI, says this is particularly pronounced among more experienced professionals:</p>
<h4 dir="ltr"><strong><em><strong id="docs-internal-guid-a162489f-7fff-4545-570c-b291d179e0c9"></strong></em></strong></h4>
<h5 dir="ltr"><em>We&rsquo;ve found that older professionals have more barriers than younger ones. They think: I&rsquo;ve been doing this job for 20 years and AI is going to come in and take over my job.</em></h5>
<p dir="ltr">But founders across the board agree: AI isn&rsquo;t here to replace people. It&rsquo;s here to support them. The real value lies in helping individuals do their jobs faster, better, and more creatively.</p>
<h5 dir="ltr"><em>If you&rsquo;re spending eight hours writing a report, AI can draft the bulk of it in ten minutes. That frees you up to focus on the parts that really matter. The real challenge is shifting perspectives away from the fear that AI is taking over the world.</em></h5>
<p dir="ltr">That shift in perspective relies on one thing above all: trust. And trust is fragile &ndash; especially when AI systems behave unpredictably or rely on complex, opaque processes. Eduardo Candela puts it plainly:&nbsp;</p>
<h5 dir="ltr"><em>If an AI gives a wrong answer, people often lose trust in the whole system.</em></h5>
<hr>
<h2><strong id="docs-internal-guid-e22ae8ef-7fff-5014-13a0-666accefa76f">Closing the Gap</strong></h2>
<p dir="ltr">For founders, one of the biggest ongoing challenges is bridging that gap. Helping users, clients, and even investors understand the reality through transparency and education is what will ultimately build trust in systems that often feel opaque.</p>
<p dir="ltr">Eduardo Candela, co-founder at Maihem, believes closing this gap starts with honesty and clarity about what AI can and can&rsquo;t do:</p>
<h5 dir="ltr"><em>We want people to confidently harness the power of AI, while also being aware of the limitations. Bridging that gap between expectations and reality is key.</em></h5>
<p>That process of building trust is especially tricky in more complex AI systems. Even a well-meaning effort to explain how it all works can end up overwhelming users. As Katya Lait explains, that means walking a fine line between transparency and information overload:</p>
<h5 dir="ltr"><em>Obviously, we want to create trust within the product, but multi-agent systems are very complicated and dense in their workflows.&nbsp;</em></h5>
<h5 dir="ltr"><em>We pull data from many sources and process them in complex ways, so we have to make tradeoffs between creating trust and not completely overwhelming them with what's going on in the background.</em></h5>
<p>Ultimately, education, design, and communication all play a role. The AI systems that succeed won&rsquo;t just be the ones that work &ndash; they&rsquo;ll be the ones people understand and believe in.</p>
<hr>
<h3 dir="ltr"><strong>Curious to learn more?</strong></h3>
<p dir="ltr">Our <a href="https://www.generativegroup.ai/insights/ai-equal-opportunities-resources/">Opportunities Hub</a> is packed full of resources to upskill and find community in the AI space.</p>
<h3><strong id="docs-internal-guid-d4679ffc-7fff-3b0e-11cd-5e5b0f2ee3f1">Building with AI?</strong></h3>
<p>Generative partners with startups at every stage to help them scale smarter, move faster, and deliver real results. <a href="https://www.generativegroup.ai/contact-us/">Find out how we work with AI startups.</a></p>

We asked founders from across the Faces of AI series to weigh in on the biggest myths they’re still encountering in conversations with clients, customers, and teams. Here’s what they told us.

The 3 BIGGEST Misconceptions About AI (Debunked by Founders)

<h4 dir="ltr">Data centres are under immense pressure, from power constraints to sustainability mandates. Cooling systems are one of their biggest energy drains &ndash; and OctaiPipe is using AI to make them significantly more efficient.</h4>
<p dir="ltr">But this isn&rsquo;t your typical AI startup story. Born from a spur-of-the-moment conversation on a train and shaped by years of deep R&amp;D, OctaiPipe has evolved from consultancy roots into a product-first company focused on federated learning &mdash; an approach that keeps data local and private, while still enabling powerful AI training at the edge.</p>
<p dir="ltr">We caught up with co-founders George Hancock, Ivan Scattergood and Eric Topham to talk about privacy-preserving AI, federated learning, and building for the market before the market&rsquo;s ready.</p>
<h2 dir="ltr">What specific problem is OctaiPipe solving, and why does it matter now?</h2>
<p dir="ltr"><strong>George:</strong> As AI demand grows, so does the pressure on the infrastructure that supports it. Data centres are facing increasing constraints around power, energy use, and sustainability &ndash; and cooling systems are one of their biggest energy drains. That&rsquo;s where we come in.&nbsp;</p>
<p dir="ltr">Our focus is to optimise energy efficiency in data centre cooling systems using AI, aiming to deliver up to 30% savings.</p>
<p dir="ltr">What makes our approach different is the use of federated learning. Our platform allows AI to be trained and deployed securely at the edge, maintaining privacy. This design has attracted attention from both customers and investors, which has naturally drawn us deeper into the data centre space. We offer a timely solution to a growing challenge.</p>
<h2 dir="ltr">Tell us about the idea behind your startup. What&rsquo;s the story there?</h2>
<p dir="ltr"><strong>Ivan:</strong> It all started on a train, really. Eric met Paul Carver while geeking out over weather maps &ndash; Eric was racing professionally at the time, and Paul was about to set sail. One thing led to another, and Paul, excited by Eric&rsquo;s background in data science, suggested they start a company.</p>
<p dir="ltr">That company turned into a successful data science consultancy. George came on board to lead commercial efforts, and I joined to help deliver projects. As part of our work, we ran an &ldquo;innovation sandbox&rdquo; where MSc students could complete their theses by working on real R&amp;D challenges for our clients.</p>
<p dir="ltr">It was during one of these projects that we began exploring federated learning &ndash; driven by a use case involving factory-floor devices producing a terabyte of data per week each. Uploading that volume to the cloud was tough, so instead of taking the data to the code, we brought the code to the data. That&rsquo;s when the concept behind OctaiPipe, our federated learning platform, was born.</p>
<p dir="ltr">The market wasn&rsquo;t quite ready for a federated learning platform on its own. What it was ready for was a compelling application of that tech. Our work with edge devices in manufacturing pointed us toward data centres.&nbsp;</p>
<p dir="ltr">Several clients nudged us in that direction, and we realised we could simulate data centre energy use and train reinforcement learning agents to optimise cooling. That&rsquo;s how OctaiPipe became what it is today: a platform quietly powered by federated learning, driving real-world energy efficiency.</p>
<h2 dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/1ad4899e-4079-46fd-b027-5312fccfc353" alt="" width="600" height="398"></h2>
<h2 dir="ltr">There&rsquo;s a lot of uncertainty around AI in the wider population. What are some of the common myths or misconceptions you hear?</h2>
<p dir="ltr"><strong>George:</strong> We often hear hesitancy to the tune of "I don&rsquo;t know it, I don&rsquo;t trust it, I don&rsquo;t want to use it"&nbsp; &ndash; especially in manufacturing, where people have real concerns about how it fits into their work.&nbsp;</p>
<p dir="ltr">There&rsquo;s also this idea that AI is something you just plug in and it works. But without upskilling and buy-in from the people using it, even the best solutions won&rsquo;t stick. Our approach with clients is always: do you actually need an AI solution? If we can&rsquo;t see a clear business case or ROI, we won&rsquo;t build it. We&rsquo;ve walked away from projects that didn&rsquo;t stack up, and some of those clients have come back later with a more focused brief.</p>
<p dir="ltr">And honestly, AI still exists in a bit of a bubble. To people outside the space, it often just means "ChatGPT" now. But there&rsquo;s a whole world beyond that. Ivan, for example, was working on ML way before it was cool.&nbsp;</p>
<p dir="ltr"><strong>Ivan:</strong> I studied cybernetics and control engineering back in 1994 and built a neural network to play the Prisoner&rsquo;s Dilemma. The maths has been around for decades. What changed was the arrival of big data and greater computing power about ten years ago. That's why there's been this massive explosion.</p>
<p dir="ltr">Back when we were a consultancy, we used to avoid saying "AI" at all. We&rsquo;d say ML, because that&rsquo;s what we were actually doing. We even had a running joke: if you&rsquo;re talking to investors, it&rsquo;s AI. If you&rsquo;re hiring, it&rsquo;s ML. And when you&rsquo;re actually building the thing, it&rsquo;s logistic regression.&nbsp;</p>
<p dir="ltr">There's a lot of hype about it but, in most situations, you don't need anything particularly complicated to help you. You just need something that works.</p>
<h2 dir="ltr">&lsquo;AI safety&rsquo; can mean very different things depending on who you talk to. What does AI safety mean to you, and how does it show up in your day-to-day?</h2>
<p dir="ltr"><strong>George:</strong> AI safety is a broad term, and its meaning really depends on who you&rsquo;re talking to &ndash; practitioners, users, commercial teams, or policymakers will all define it differently. For us, it&rsquo;s about building AI systems that are explainable and trustworthy.</p>
<p dir="ltr">Last year, we worked on an Innovate UK initiative to unpack this idea. We looked at how terms like &ldquo;AI safety&rdquo; and &ldquo;AI ethics&rdquo; are often used interchangeably, and we built a comprehensive framework around the principles that matter most to us &ndash; things like transparency, interpretability, and user confidence.</p>
<p dir="ltr">That thinking carried through into a project with P&amp;G, where we focused on practical ways to make AI outputs understandable and reliable. Not just technically sound, but usable and trusted by the people interacting with them.&nbsp;</p>
<h2 dir="ltr">What&rsquo;s been the biggest challenge in bringing an AI product like yours to market at scale?</h2>
<p dir="ltr"><strong>George: </strong>Market maturity. We&rsquo;ve always been slightly ahead, working on solutions 18 months before the market&rsquo;s really ready for them. That edge has come from staying close to research and applying data science deeply, but it&rsquo;s also meant we&rsquo;ve had to shift focus to more immediate, tangible applications.&nbsp;</p>
<p dir="ltr">The challenge isn&rsquo;t whether AI can help. It&rsquo;s whether the market recognises the problem it&rsquo;s solving, right now.</p>
<p dir="ltr"><strong>Eric: </strong>I&rsquo;ll put it another way: 99% of people talking about AI don&rsquo;t really know what they&rsquo;re talking about. That makes scaling difficult, because most organisations don&rsquo;t know what they&rsquo;re buying or how to be ready for it.</p>
<p dir="ltr">It&rsquo;s not just about technical integration. It&rsquo;s about embedding AI into business processes. You can build a brilliant churn prediction model, but if the business doesn&rsquo;t know what to do with that prediction, it&rsquo;s useless. And too often, rather than saying &ldquo;we weren&rsquo;t ready,&rdquo; people blame the application.</p>
<p dir="ltr">So, yes, it&rsquo;s a maturity problem. Even now, as awareness grows, most people still struggle to frame the use case, or measure its impact in commercial terms.</p>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/7edcc2f1-801c-4b66-bcaa-0f4846528d41" alt="" width="600" height="312"></p>
<h2 dir="ltr">Is it possible to have the traditional 3&ndash;5 year business plan in a sector like AI?</h2>
<p dir="ltr"><strong>Eric: </strong>I&rsquo;d say the idea that &ldquo;everything changes too quickly for long-term planning&rdquo; mainly applies to the world of LLMs, where there&rsquo;s a well-funded arms race driving rapid iteration.</p>
<p dir="ltr">But outside of that bubble, there are slower-moving, longer-term trends &ndash; like edge computing and the ability to run machine learning on small, distributed devices. Those shifts take time because they rely on complex systems maturing and integrating together.</p>
<p dir="ltr">When George says we&rsquo;ve been operating 18 months ahead of the market, I&rsquo;d argue it&rsquo;s often further. We&rsquo;ve been building toward a distributed machine learning paradigm for years: models that don&rsquo;t rely on massive, centralised datasets in the cloud, but instead train locally on devices like mobile phones. It&rsquo;s a direction that supports data privacy, sovereignty, and trust. These are all issues that matter increasingly to individuals, businesses, and governments alike.</p>
<p dir="ltr">So yes, some areas of AI are evolving quickly.&nbsp; LLMs release every few weeks, but even those models are borrowing ideas like quantisation from edge AI, where constraints like limited memory have been long-standing design challenges.</p>
<p dir="ltr">What we&rsquo;re seeing is the growing viability of scalable, distributed AI &ndash; something we&rsquo;ve been ahead of the curve on for some time. And in that space, yes, you can plan for the long term because you're building on maturing trends, not chasing hype.</p>
<h2>You&rsquo;re now a team of 15. What has the talent attraction process been like, and how has it evolved?</h2>
<p dir="ltr"><strong>Eric: </strong>We&rsquo;ve shifted a lot as a company. In the early days, we were more service-based &ndash; building bespoke solutions for others &ndash; so we hired a lot of sharp, junior talent straight out of top universities. The recruitment focus then was all about raw technical ability.</p>
<p dir="ltr">Now, as we&rsquo;ve transitioned into a deep-tech, product-led company, we look for experienced specialists with domain expertise. The process has become more about understanding how someone approaches design and problem-solving. Can they navigate complexity, not just code?</p>
<p dir="ltr">If someone shows up and can&rsquo;t code, we&rsquo;ll figure that out pretty quickly and they won&rsquo;t be around for long. So it&rsquo;s less about testing fundamentals and more about bringing in people who already know how to apply them at a high level.</p>
<h2 dir="ltr">Finally, you're obviously very busy people. What can we find you doing in your downtime?</h2>
<p dir="ltr"><strong>Eric: </strong>Thinking about work.&nbsp;</p>
<p dir="ltr"><strong>George: </strong>Yeah, ringing each other to chat about what we need to do next!&nbsp;</p>
<p dir="ltr"><strong>Eric:</strong> But when I do switch off, I like exploring Paris with my wife or going climbing.</p>
<p dir="ltr"><strong>Ivan:</strong> I train in kung fu two or three times a week &ndash; I&rsquo;ve been training with my current Shifu for eight years. Before that, it was Taekwondo, Wing Chun, boxing&hellip; martial arts have been a big part of my life since my twenties. I do a fair bit of mountain biking as well.</p>
<p dir="ltr"><strong>George:</strong> I used to be big on gym, swim, and exercise. But since my daughter arrived last July, most of my time off is spent on daddy daycare duty to give my wife a well-earned break!</p>
<hr>
<p dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p class="article-editor-paragraph"><strong>OctaiPipe is one of the 54 innovative AI organisations featured in our 'Faces of AI 2025' report, which is available to </strong><a class="article-editor-link zSvKgyodXUoGbhUhxSWpxUXaFuhWtTKexrM " href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" rel="noopener noreferrer"><strong>download for free now</strong></a><strong>.</strong></p>
<p class="article-editor-paragraph article-editor-content__has-focus"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="article-editor-link zSvKgyodXUoGbhUhxSWpxUXaFuhWtTKexrM " href="https://www.generativegroup.ai/contact-us/" rel="noopener noreferrer"><strong>let's talk.</strong></a></p>

Cooling systems for data centres consume huge amounts of energy. OctaiPipe is taking on the challenge with AI-powered federated learning

Cool Heads, Cooler Systems: The Startup Making AI Work for Energy Efficiency

<h3 id="ember219" class="ember-view reader-text-block__paragraph"><a id="ember220" class="ember-view" href="https://www.linkedin.com/in/jonathanrhyslow/">Jonathan Low</a> <strong>and </strong><a id="ember221" class="ember-view" href="https://www.linkedin.com/in/jakobcassiman/">Jakob Cassiman</a><strong>, co-founders of </strong><a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.linkedin.com/company/scopeinspection/" data-test-app-aware-link="">Scope</a><strong>, were outsiders to the Testing, Inspection, and Certification (TIC) industry &ndash; and that&rsquo;s exactly what gives them their edge. </strong></h3>
<p id="ember222" class="ember-view reader-text-block__paragraph">They&rsquo;re redesigning the inspection process for industries still reliant on pen, paper, and outdated tech. Scope builds AI-powered tools that cut cycle times by up to 45%, freeing inspectors to focus on decision-making over admin.</p>
<p id="ember223" class="ember-view reader-text-block__paragraph">They&rsquo;ve only just begun, but the potential to disrupt the sector is huge. We caught up with Jonathan to hear how Scope went from an idea to a fast-growing company working with some of the biggest names in TIC.</p>
<h3 id="ember224" class="ember-view reader-text-block__heading-3">Could you be a key player in Scope&rsquo;s founding team?</h3>
<p id="ember225" class="ember-view reader-text-block__paragraph">Generative has partnered exclusively with Scope to hire for key London-based roles in AI and engineering. If you're ready to help reshape the $250bn inspection industry, get in touch with <a id="ember226" class="ember-view" href="https://www.linkedin.com/in/dan-clouting/">Dan Clouting</a>.</p>
<h2 id="ember227" class="ember-view reader-text-block__heading-2">Let&rsquo;s talk about the origins of Scope. How did you and Jakob come together?</h2>
<p id="ember228" class="ember-view reader-text-block__paragraph">Both of us are really ambitious people from technical backgrounds. I used to work at Conjecture, focusing on document processing and building tools to make AI systems more controllable. And Jakob was a machine learning engineer working with physical data.</p>
<p id="ember229" class="ember-view reader-text-block__paragraph">We both knew we wanted to start a company, so we left our jobs and joined a start-up program called Entrepreneur First in London; they introduce you to other aspiring founders and you work on exploring problems and developing products together.</p>
<p id="ember230" class="ember-view reader-text-block__paragraph">We started building AI tools to search documents like PDFs, Excels and other structured data formats, before leaning into the TIC market.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/dbd68f25-0a63-497f-b551-34e08b787274" alt="" width="600" height="568"></p>
<h2 id="ember232" class="ember-view reader-text-block__heading-2">How did Scope end up getting into the TIC industry?</h2>
<p id="ember233" class="ember-view reader-text-block__paragraph">One of our early customers was a large inspection company and the positive reaction we got after working with them was <em>incredible.</em></p>
<p id="ember234" class="ember-view reader-text-block__paragraph">We spoke to an inspector on their team who carried a hefty manual of standards she had to reference during every inspection. After trying the tool for the first time, she said, &ldquo;Wow, I don't need this anymore&rdquo; and threw the book away.</p>
<p id="ember235" class="ember-view reader-text-block__paragraph">It was a small moment that spoke volumes.</p>
<p id="ember236" class="ember-view reader-text-block__paragraph">After this experience, we started talking to more people in the TIC space, and realised it's an industry that's been stuck with dated systems for far too long. We saw an opportunity to create value and solve real problems &ndash; so we decided to double down on TIC.</p>
<h2 id="ember238" class="ember-view reader-text-block__heading-2">What&rsquo;s the biggest problem that Scope helps inspectors solve?</h2>
<p id="ember239" class="ember-view reader-text-block__paragraph">Inspectors spend most of their time on planning, creating reports, and data retrieval for their next inspection.</p>
<p id="ember240" class="ember-view reader-text-block__paragraph">We build tools that automate the time-intensive parts of the process, enabling inspectors to spend more time on decision making. This pays off for our customers: we reduce their cycle time by 45% and get average reporting times down to 12 minutes. Without compromising on the quality of the work.</p>
<p id="ember241" class="ember-view reader-text-block__paragraph">We talk to companies with 100,000 people, who'll admit, &ldquo;Yeah, we still do everything on pen and paper&rdquo;. The reality is, the software that inspectors are using is built for other people. It's built for people in factories, it's built for maintenance experts. Inspectors have been incredibly underserved by tech solutions.</p>
<h2 id="ember243" class="ember-view reader-text-block__heading-2">What's the most exciting technical challenge that you're dealing with at the moment?</h2>
<p id="ember244" class="ember-view reader-text-block__paragraph">Something that&rsquo;s difficult in the inspection space is dealing with a lot of different workflows across customers. Inspecting a t-shirt on a production line is very different from inspecting a power plant. So, we build software that can work for different types of customers. That's a challenge that's been pretty interesting for us to adapt to.</p>
<p id="ember245" class="ember-view reader-text-block__paragraph">We make bespoke systems for each customer. We've got machine learning engineers who ingest everything from PDF data to Excel data; we use that to automate their workflows. That&rsquo;s why the companies we work with love our solution. We're embedded in their systems.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/8eec0f8d-22d8-4480-807f-f71d0ffbcfec" alt="" width="600" height="400"></p>
<h2 id="ember248" class="ember-view reader-text-block__heading-2">As a startup what are you finding the most difficult at the moment?</h2>
<p id="ember249" class="ember-view reader-text-block__paragraph">Good question. At the moment it&rsquo;s hiring&hellip; we have a really high bar. We've hired people from DeepMind, Microsoft and Amazon and want every new hire to make the whole team better.</p>
<p id="ember250" class="ember-view reader-text-block__paragraph">We're ambitious, doing big things, and striving for excellence. The people that join Scope are motivated and intelligent, so it&rsquo;s a challenge to find people with the right skills and mindset.</p>
<p id="ember251" class="ember-view reader-text-block__paragraph">The people we interview are always really excited about working with us. Obviously there&rsquo;s the technical challenge of building these tools, which is attractive to lots of people. But it's about more than that: our users say that it saves them their weekends and gives them more time back with family. Making that difference is something we all find incredibly fulfilling.</p>
<h2 id="ember253" class="ember-view reader-text-block__heading-2">In terms of scaling the product that you've built, what's the main challenge at the moment?</h2>
<p id="ember254" class="ember-view reader-text-block__paragraph">We've taken a very modular approach to development to solve different issues. It can be difficult because most inspection workflows are unique. So, we've been through many iterations.</p>
<p id="ember255" class="ember-view reader-text-block__paragraph">Now, as we scale, the challenge is to make sure that the data layer stays consistent so we're able to onboard customers faster and make it easier for them to make adjustments to their reports and workflows.</p>
<p id="ember256" class="ember-view reader-text-block__paragraph">As a small team, we've been able to stay very customer focused. As we scale, we want to keep that mindset &ndash; ensuring that everyone on the team gets the same level of customer involvement as we do now. It&rsquo;s something that we're going to keep at the core of our business as we grow.</p>
<h2 id="ember257" class="ember-view reader-text-block__heading-2">How do you see your technology evolving over the next few years? And how will it change what you've built so far?</h2>
<p id="ember258" class="ember-view reader-text-block__paragraph">We know that language models and AI systems will continue to get better. We've seen a steady increase in how these models perform, so I expect that more of our work can be automated in the future. That&rsquo;ll create opportunities for the businesses we work with.</p>
<p id="ember259" class="ember-view reader-text-block__paragraph">I see Scope evolving into a platform where businesses can take the data that we gather like all the instructions for a product, and then build their own custom analysis and calculations on top of the data.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/704dc4fe-23e0-4ea3-a73b-60b851973353" alt="" width="600" height="400"></p>
<h2 id="ember260" class="ember-view reader-text-block__heading-2">You&rsquo;ve got a clear vision for how the product will evolve as you scale - but how do you see the company changing?</h2>
<p id="ember261" class="ember-view reader-text-block__paragraph">At the moment, we&rsquo;re looking to make a few key engineering hires to scale the team. We&rsquo;re on the lookout for people with the right AI skill set, but mindset is just as important for us.</p>
<p id="ember262" class="ember-view reader-text-block__paragraph">We know nothing worth doing is easy, so everyone on the team needs to be passionate about solving real world problems.</p>
<p id="ember263" class="ember-view reader-text-block__paragraph">While we&rsquo;re 10x oversubscribed on our Pre-Seed funding, we predict we'll be raising a Series A in the next 9-to-12 months. We're aiming to have more than a million dollars in revenue in 2025, and &ndash; if we hit our growth aims by mid-2026 &ndash; we&rsquo;ll be on track to be doing 2-to-3 million dollars in recurring revenue, which is so exciting.</p>
<p id="ember264" class="ember-view reader-text-block__paragraph">As a part of the Series A fundraising, we'll be expanding to the US. We have a couple of customers out there who are eager to get involved in what we're doing. One day, we'll have deployment engineers in the Middle East and Asia too. Our ultimate aim is to be working with inspectors around the world.</p>
<h3 id="ember265" class="ember-view reader-text-block__heading-3">Scope is hiring!</h3>
<p id="ember266" class="ember-view reader-text-block__paragraph">Work on real-world AI with a pre-seed startup backed by tier-one investors. Contact <a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.linkedin.com/in/dan-clouting/?lipi=urn%3Ali%3Apage%3Ad_flagship3_company_posts%3BXL%2Fa1Xp%2FSt2h2foMBgxJ6w%3D%3D" target="_self" data-test-app-aware-link="">Dan Clouting</a> to learn more.</p>
<h2 id="ember267" class="ember-view reader-text-block__heading-2">When it comes to AI trends, what are you most excited about?</h2>
<p id="ember268" class="ember-view reader-text-block__paragraph">What excites me? This is really niche, but I'm quite excited by OCR (Optical Character Recognition).</p>
<p id="ember269" class="ember-view reader-text-block__paragraph">We&rsquo;re getting really good at being able to interpret really ugly hand-written documents, which means we can take a lot of data that's just written down and locked away in a filing cabinet somewhere and turn it into really useful data.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/9567ea09-3068-4140-969b-fd62acf49b2e" alt="" width="600" height="400"></p>
<h2 id="ember271" class="ember-view reader-text-block__heading-2">And what do you feel is overhyped?</h2>
<p id="ember272" class="ember-view reader-text-block__paragraph">I think agent frameworks are overhyped. A lot of people talk about AI agents and making them work, but so far, we haven't really seen enough reliability to make it work in an enterprise setting.</p>
<p id="ember273" class="ember-view reader-text-block__paragraph">While it may work for simple tasks, there's a lot of steps in more complex tasks where things can go wrong.</p>
<h2 id="ember275" class="ember-view reader-text-block__heading-2">What's the best advice you've ever received about leading a tech company and a startup?</h2>
<p id="ember276" class="ember-view reader-text-block__paragraph">The best advice I&rsquo;ve had while building Scope is to build a product that people actually need. Something that <em>genuinely</em> fixes a problem for people.</p>
<p id="ember277" class="ember-view reader-text-block__paragraph">It&rsquo;s easy to think about solutions and then try to find people that need that solution. But you should speak to people, find real problems, and <em>then</em> think about how you can build a solution to fix that problem.</p>
<h2 id="ember278" class="ember-view reader-text-block__heading-2">You&rsquo;re obviously incredibly busy. How do you switch off and relax outside of work?</h2>
<p id="ember279" class="ember-view reader-text-block__paragraph">Jakob and I do a lot of running. He recently did a marathon in Europe and I&rsquo;d like to have a go at the London Marathon one day, but it&rsquo;s just so hard to get into.</p>
<p id="ember280" class="ember-view reader-text-block__paragraph">I also love swimming. I do a lot of in-pool swimming, but when I can, I&rsquo;ll go open-water swimming. I&rsquo;ve also tried my hand at some long distance swimming when I&rsquo;ve had the opportunity. A few months ago, I went for a swim across a huge lake in Wales in the middle of winter, which was incredible, but also a <em>big</em> challenge and pretty scary at times!</p>
<h2 id="ember281" class="ember-view reader-text-block__heading-2">Finally, if you weren't working at Scope, what do you think you would be doing now?</h2>
<p id="ember282" class="ember-view reader-text-block__paragraph">Before founding Scope, I knew that I wanted to start a business. That&rsquo;s why I left my job and joined the Entrepreneur First program&hellip; but it&rsquo;s interesting to think where I&rsquo;d be if things turned out differently.</p>
<p id="ember283" class="ember-view reader-text-block__paragraph">If I wasn&rsquo;t building Scope and solving problems for the TIC industry, I'd probably be building another company doing something with AI. There's a lot of interesting problems out there that can be solved with technology and AI, so I&rsquo;d like to think if I wasn&rsquo;t fixing problems in the inspections process, I&rsquo;d still want to be fixing problems elsewhere.</p>
<h2 id="ember284" class="ember-view reader-text-block__heading-2">Want to be part of the team revolutionising TIC?</h2>
<div class="reader-image-block reader-image-block--full-width">
<p><img src="https://cdn.sourceflow.co.uk/__gallery/be8d77f4-5c44-4503-b297-585b45ea0490" alt="" width="600" height="600"></p>
<p id="ember286" class="ember-view reader-text-block__paragraph">Are you a driven AI Engineer, looking to make an impact and solve problems with technology? <a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.linkedin.com/company/generativegroups/" target="_self" data-test-app-aware-link="">Generative</a> has partnered exclusively with <a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.linkedin.com/company/scopeinspection/" target="_self" data-test-app-aware-link="">Scope</a> to find top talent for three critical roles:</p>
<p id="ember287" class="ember-view reader-text-block__paragraph">👉 Applied AI Engineer (&pound;90K&ndash;&pound;130K + equity)</p>
<p id="ember288" class="ember-view reader-text-block__paragraph">👉 Founding Full Stack Engineer (&pound;80K&ndash;&pound;120K + equity)</p>
<p id="ember289" class="ember-view reader-text-block__paragraph">👉 Forward Deployed Engineer (&pound;80K&ndash;&pound;120K + equity)</p>
<p id="ember290" class="ember-view reader-text-block__paragraph">These are permanent, London-based opportunities (Covent Garden) and offer a rare chance to get in early at a 10x oversubscribed pre-seed success story, backed by tier-one investors.</p>
<p id="ember291" class="ember-view reader-text-block__paragraph">📩 Get in touch with <a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.linkedin.com/in/dan-clouting/?lipi=urn%3Ali%3Apage%3Ad_flagship3_company_posts%3BXL%2Fa1Xp%2FSt2h2foMBgxJ6w%3D%3D" target="_self" data-test-app-aware-link="">Dan Clouting</a> / <a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="mailto:dan.clouting@generativegroup.ai" target="_self" data-test-app-aware-link="">dan.clouting@generativegroup.ai</a> to find out more.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="600" height="322"></p>
<p id="ember293" class="ember-view reader-text-block__paragraph"><strong>Scope is one of the 54 innovative AI organisations featured in our 'Faces of AI 2025' report, which is available to </strong><a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now</strong></a><strong>.</strong></p>
<p id="ember294" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="UCfvfNsyTpsPQidhUnqqzZLAaQtxAVUA " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link=""><strong>let's talk.</strong></a></p>
<figure class="reader-image-block__figure"><a href="https://www.linkedin.com/posts/generativegroups_scope-x-generative-activity-7323270478075232256-AP7q?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAABgfqgoBCfoqMBKUwKk7zyapkunRbJbrdKY" target="_blank" rel="noopener noreferrer">
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        ">&nbsp;</div>
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</a></figure>
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Jonathan Low and Jakob Cassiman, co-founders of Scope, were outsiders to the Testing, Inspection, and Certification (TIC) industry – and that’s exactly what gives them their edge. 

Disrupting a $250bn Industry: How Scope is Helping Firms Ditch Pen and Paper for AI

<h2 id="ember2727" class="ember-view reader-text-block__heading-2">While AI continues to evolve, Eduardo Candela is on a mission to ensure it&rsquo;s used with care, clarity, and confidence.</h2>
<p id="ember2728" class="ember-view reader-text-block__paragraph">As the co-founder and CTO of Maihem, his priority is clear: help enterprises embrace AI with confidence, bridging the gap between cutting-edge technology and real-world deployment.</p>
<p id="ember2729" class="ember-view reader-text-block__paragraph">We sat down with Eduardo&nbsp;to hear more about his mission, the challenges of building trustworthy AI, and how his PhD and industry experience laid the perfect foundation for his entrepreneurial journey.</p>
<hr>
<h3 id="ember2731" class="ember-view reader-text-block__heading-3">Let&rsquo;s talk about the origins of Maihem &ndash; how did the idea come about?</h3>
<p id="ember2732" class="ember-view reader-text-block__paragraph">I started my career in the automotive industry, working in Silicon Valley at Tesla, and then later at Bosch Centre of AI. That&rsquo;s where I saw firsthand what we call mission-critical AI: systems being deployed in cars, where safety and performance are essential. It became clear how important it is to not just build powerful AI, but to keep it safe and under control.</p>
<p id="ember2733" class="ember-view reader-text-block__paragraph">Before I worked in Silicon Valley, I did my Masters at MIT, where I also conducted research on using AI in mission-critical decision-making processes. Five years ago, I moved to London to pursue my PhD at Imperial College London to research safety in self-driving cars, specifically how to measure risk and train models to be risk-aware and reliable using reinforcement learning.</p>
<p id="ember2734" class="ember-view reader-text-block__paragraph">Max, my co-founder, took a different path. He was at McKinsey before starting a PhD in Natural Language Processing, where his research focused on how to make generative AI safer &ndash; specifically, how to detect and prevent the spread of conspiracy theories.</p>
<p id="ember2735" class="ember-view reader-text-block__paragraph">We met while still in our PhDs and we immediately connected over a shared passion and a shared question: how do we close the gap between AI research, and real and responsible deployment? <strong>Maihem</strong> became our answer. It&rsquo;s a way to take everything we learned in research and apply it to help companies deploy AI with confidence.</p>
<h3 id="ember2737" class="ember-view reader-text-block__heading-3">How do you think your background in academia has shaped your startup journey?</h3>
<p id="ember2738" class="ember-view reader-text-block__paragraph">When I left my job in Silicon Valley to pursue a PhD, people thought I was crazy&hellip; walking away from the money and the title. But I knew I wanted to live in the future, to go deep on the questions I cared about. A PhD gave me that.</p>
<p id="ember2739" class="ember-view reader-text-block__paragraph">It&rsquo;s still not common for people in academia to start startups. But for me, it makes perfect sense. You're using science to test ideas, you&rsquo;re running experiments, you&rsquo;re validating things, failing, refining, and spending years going very deep to solve a very specific problem that nobody has solved before. That mindset is exactly what you need to build something from scratch.</p>
<p id="ember2740" class="ember-view reader-text-block__paragraph">Both my co-founder and I completed PhDs, and we&rsquo;ve found that background to be incredibly valuable. It&rsquo;s a huge investment of time and energy, so you have to be really clear about what you want to get out of it. But if you are, it&rsquo;s absolutely worth it.</p>
<p id="ember2741" class="ember-view reader-text-block__paragraph">So while it doesn&rsquo;t have to be a PhD, I really encourage anyone who&rsquo;s passionate about answering hard questions and uncovering truth to consider startups.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/b8136b3a-10eb-4cc5-bae4-b71178cc6d32" alt="" width="600" height="400"></p>
<h3 id="ember2743" class="ember-view reader-text-block__heading-3">There's a lot of uncertainty around AI within the wider population. From your perspective, what are some of the most common misconceptions out there?</h3>
<p id="ember2744" class="ember-view reader-text-block__paragraph">We see it across the board &ndash; people are very aware of AI&rsquo;s power, but there&rsquo;s still a lot of skepticism around it. One of the key things many people don&rsquo;t realise is that these new models are <em>probabilistic</em>. You can give them the same input twice and get two completely different outputs.</p>
<p id="ember2745" class="ember-view reader-text-block__paragraph">That unpredictability can be hard to wrap your head around when you&rsquo;re expecting consistency. Hallucinations are one of the biggest blockers to adoption right now. When an AI gives users a wrong answer, people often lose trust in the entire system and immediately disengage.</p>
<p id="ember2746" class="ember-view reader-text-block__paragraph">Of course, there&rsquo;s a more technical layer to this too, where models can be trained in the wrong direction. But for most users and businesses, the biggest challenge is just getting these systems to perform as<em> </em>expected.</p>
<p id="ember2747" class="ember-view reader-text-block__paragraph">There&rsquo;s a real gap between what people <em>think</em> AI should be capable of and how these technologies actually work. They&rsquo;re still not perfect. We want people to confidently harness the power of AI, while also being aware of the limitations. Bridging that gap between expectations and reality is key.</p>
<h3 id="ember2749" class="ember-view reader-text-block__heading-3">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h3>
<p id="ember2750" class="ember-view reader-text-block__paragraph">One of the biggest challenges we&rsquo;ve been tackling is how to bring user feedback and preferences directly into how AI systems are built and behave.</p>
<p id="ember2751" class="ember-view reader-text-block__paragraph">Right now, AI gets developed by engineers, it&rsquo;s deployed, and then users interact with something that doesn&rsquo;t always meet their expectations. So we&rsquo;ve been asking: how do we close that loop? How do we make users feel in control, and actually get what they want from these systems?</p>
<p id="ember2752" class="ember-view reader-text-block__paragraph">It&rsquo;s really a human&ndash;AI alignment problem, and solving it is key if we want people to trust and adopt these tools.</p>
<h3 id="ember2753" class="ember-view reader-text-block__heading-3">&lsquo;AI Safety&rsquo; can mean very different things to different people. What does that term mean to you, and what does it look like in practice?</h3>
<p id="ember2754" class="ember-view reader-text-block__paragraph">That&rsquo;s a great question. For me, one of the key realisations &ndash; especially during my PhD research on self-driving cars &ndash; is that safety is about performance under constraints.</p>
<p id="ember2755" class="ember-view reader-text-block__paragraph">When I used to run simulations, the safest car was the one that just parked and never moved. Technically, that&rsquo;s &ldquo;safe&rdquo; but it&rsquo;s also useless. All of us, when we take a plane, when we drive a car, when we go out, we're always accepting some level of risk in order to achieve a goal.</p>
<p id="ember2756" class="ember-view reader-text-block__paragraph">The question then becomes: how do we achieve a goal without crossing certain boundaries? How do we maintain control? That&rsquo;s what AI safety looks like to me. The real challenge comes in defining and measuring those limits, and ensuring users feel they are in control.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/561c8268-1e75-422b-8392-81f08709d05a" alt="" width="600" height="400"></p>
<h3 id="ember2758" class="ember-view reader-text-block__heading-3">What is the biggest challenge in bringing AI products like yours to market?</h3>
<p id="ember2759" class="ember-view reader-text-block__paragraph">The biggest challenge (and the biggest opportunity) is the gap between the development of cutting-edge AI and real-world adoption.</p>
<p id="ember2760" class="ember-view reader-text-block__paragraph">You look at the headlines and see OpenAI, new models, new agents, new startups. But when you talk to enterprises &ndash; and the everyday users within their companies &ndash; there&rsquo;s often a huge disconnect. Most companies don&rsquo;t have the talent, the understanding, or the confidence to use these tools effectively.</p>
<p id="ember2761" class="ember-view reader-text-block__paragraph">I call this the &ldquo;chasm of adoption&rdquo; and that&rsquo;s where we come in to bridge the gap. It&rsquo;s not just about technology, it&rsquo;s about mindset. A big part of the work is education: helping people understand how these systems work, and how to use them safely and effectively.</p>
<h3 id="ember2763" class="ember-view reader-text-block__heading-3">How do you see your technology evolving over the next few years?</h3>
<p id="ember2764" class="ember-view reader-text-block__paragraph">AI will continue to improve and become embedded in every part of life. Our mission is to make sure that progress benefits everyone by making AI safe and trustworthy.</p>
<p id="ember2765" class="ember-view reader-text-block__paragraph">In the short term, we&rsquo;re seeing a flood of new models, agents, workflows &ndash; both open and closed source. But most of what&rsquo;s out there today is still what we&rsquo;d call level one or two autonomy. These tools are co-pilots. They support humans, augment their work, but don&rsquo;t operate independently.</p>
<p id="ember2766" class="ember-view reader-text-block__paragraph">At some point, there&rsquo;s going to be a shift. We don&rsquo;t know exactly when, but we&rsquo;ll move into true autonomy, where these systems don&rsquo;t just assist &ndash; they act on our behalf.&nbsp; That&rsquo;s the big opportunity for us.</p>
<p id="ember2767" class="ember-view reader-text-block__paragraph">Once agents become autonomous, you need to know: are they safe? Are they in control? Can they interact with each other reliably? We&rsquo;re not there yet, but the foundations are being built now. Our goal is to help organisations prepare &ndash; so when autonomy becomes the norm, they&rsquo;re ready.</p>
<div class="reader-image-block reader-image-block--full-width"><img src="https://cdn.sourceflow.co.uk/__gallery/30a048e8-1394-4323-9b1e-7feb14b08c89" alt="" width="400" height="400"></div>
<div class="reader-image-block reader-image-block--full-width">
<h3 id="ember2769" class="ember-view reader-text-block__heading-3">When it comes to AI trends, what are you most excited about?</h3>
<p id="ember2770" class="ember-view reader-text-block__paragraph">I did my PhD in reinforcement learning, so I&rsquo;ve been close to it for a while. It&rsquo;s exciting to see it finally gaining more attention; I find it very promising. Everyone&rsquo;s talking about it now because it mirrors how humans learn: through rewards and feedback.</p>
<p id="ember2771" class="ember-view reader-text-block__paragraph">With the rise of new models like DeepSeek and others, reinforcement learning is proving to be a really powerful and accessible way to improve agent behaviour. It&rsquo;s a current trend that&rsquo;ll only grow further.</p>
<h3 id="ember2772" class="ember-view reader-text-block__heading-3">And what do you feel is overhyped?</h3>
<p id="ember2773" class="ember-view reader-text-block__paragraph">We hear a lot of talk of AI being super dangerous or close to taking over the world. But that&rsquo;s just not where we are. Especially with LLMs, people sometimes forget that these are just models trained to predict the next token, the next word.</p>
<p id="ember2774" class="ember-view reader-text-block__paragraph">We&rsquo;re nowhere near Artificial General Intelligence (AGI). These systems are not self-improving, they use huge amounts of energy, and they&rsquo;re still far away from replicating human intelligence in many domains. So while LLMs are powerful tools, we&rsquo;ll likely need different, more powerful architectures to get anywhere close to AGI.</p>
<h3 id="ember2776" class="ember-view reader-text-block__heading-3">Maihem is currently a team of five. How has the talent attraction process been for you as a startup?</h3>
<p id="ember2777" class="ember-view reader-text-block__paragraph">It&rsquo;s really exciting, but challenging. Hiring for a startup is nothing like hiring for a big company. I&rsquo;ve done both, and they&rsquo;re completely different worlds. You talk to people coming out of Big Tech and often, they just don&rsquo;t have the mindset or culture fit for a startup.</p>
<p id="ember2778" class="ember-view reader-text-block__paragraph">What you&rsquo;re really looking for is your own SWAT team: strong generalists who are smart, driven, and deeply passionate about the mission. We&rsquo;ve been really lucky with the team we&rsquo;ve assembled. Most of them have been founders themselves, so they already understand what it takes to build something from scratch.</p>
<p id="ember2779" class="ember-view reader-text-block__paragraph">That founder mindset has made a huge difference. Instead of chasing the obvious CVs, we looked for people who genuinely <em>want</em> to prove themselves and make a difference. That&rsquo;s where we&rsquo;ve found the most success.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/99c75b27-56cd-4e35-9240-86a784b30068" alt="" width="400" height="400"></p>
<h3 id="ember2781" class="ember-view reader-text-block__heading-3">You&rsquo;re obviously incredibly busy. How do you switch off and relax outside of work?</h3>
<p id="ember2782" class="ember-view reader-text-block__paragraph">For me, work-life balance isn&rsquo;t about separating work from life. Finding passion in what you do makes all the difference.</p>
<p id="ember2783" class="ember-view reader-text-block__paragraph">I&rsquo;ve always loved diving deep into tough problems; staying up late solving something challenging never felt like a chore. I love reading, especially about startups and tech. It&rsquo;s not work for me, it&rsquo;s real curiosity.</p>
<p id="ember2784" class="ember-view reader-text-block__paragraph">I also love music; I play piano and guitar &ndash; it puts my brain in a different mode and often helps me solve problems in unexpected ways. And of course, I try to stay active. I play football every weekend and tennis when I can. That's how I keep my energy up!</p>
<h3 id="ember2785" class="ember-view reader-text-block__heading-3">Finally, if you weren't working on Maihem, what other problems would you be trying to solve with AI?</h3>
<p id="ember2786" class="ember-view reader-text-block__paragraph">My passion and career have always been focused on one thing: how to build systems that make smart, automated decisions. Even before everyone was calling it &ldquo;AI,&rdquo; that&rsquo;s what I was drawn to.</p>
<p id="ember2787" class="ember-view reader-text-block__paragraph">So if I weren&rsquo;t focused on helping companies deploy AI safely and responsibly, I&rsquo;d probably be building something similar myself &ndash; maybe a vertical agent tackling a specific, meaningful and safety-critical use case.</p>
<p id="ember2788" class="ember-view reader-text-block__paragraph">I love the idea of building AI that helps people with their mental health, or invest their savings safely. But right now, my goal is to help all of these organisations first, to maximise my impact in the world.</p>
<hr>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400"></p>
<p id="ember2790" class="ember-view reader-text-block__paragraph"><strong>📥 Eduardo is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to </strong><a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now.</strong></a></p>
<p id="ember2791" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link=""><strong>let's talk.</strong></a></p>
</div>

Eduardo Candela is on a mission to ensure AI is used with care, clarity, and confidence.

Why Trust, Not Tech, Is AI’s Biggest Challenge: Eduardo Candela on Founding Maihem

<h2 dir="ltr">Building a startup is tough, but Roshan Tamil Sellvan is working smarter and harder.</h2>
<p id="ember817" class="ember-view reader-text-block__paragraph">Alongside his co-founder Alan, he launched AdvisoryAI&nbsp;to transform the world of wealth management. Instead of building another AI chatbot, they developed a system that <em>learns from every interaction</em>, adapts to financial advisors&rsquo; unique styles, and stays in line with tough regulatory standards &ndash; saving hours of manual work.</p>
<p id="ember818" class="ember-view reader-text-block__paragraph">We spoke with Roshan about the surprising way he found his perfect co-founder, how embracing a &lsquo;lazy&rsquo; mindset became a secret weapon, and what&rsquo;s next for AdvisoryAI.</p>
<hr>
<h2 dir="ltr">What specific problem is your startup solving, and why does it matter now more than ever?</h2>
<p id="ember820" class="ember-view reader-text-block__paragraph">AI is no longer some futuristic concept. Tools like ChatGPT have made everyone realise that AI can write your emails, summarise your documents, and even help plan your next holiday. So why not bring that same magic into financial advising?</p>
<p id="ember821" class="ember-view reader-text-block__paragraph">But wealth management is a whole different beast. It's full of strict regulations, complex documentation, and professionals who&rsquo;ve been doing things the same way for decades. Many of them are brilliant at what they do, but not exactly thrilled about learning new tech.</p>
<p id="ember822" class="ember-view reader-text-block__paragraph">That&rsquo;s where AdvisoryAI comes in. We&rsquo;re not just throwing a chatbot into the mix and calling it innovation. We're building an AI that actually understands the advisor&rsquo;s workflow, captures the nuances of client conversations, and generates fully compliant reports. All without the back-and-forth prompt wrangling.</p>
<p id="ember823" class="ember-view reader-text-block__paragraph">My co-founder Alan ran a financial advisory firm for years, so he saw the pain points up close. Writing suitability reports, annual reviews, meeting notes... It's all incredibly time-consuming. Sure, AI <em>can</em> do it, but we&rsquo;ve gone a step further. We&rsquo;re training it to do it <em>right</em>.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/ccf70cd2-1f2d-458f-a9f3-bbb397e36ef9" alt="" width="400" height="400"></p>
<h2 class="ember-view reader-text-block__paragraph">How did you and your co-founder, Alan, meet?&nbsp;</h2>
<p id="ember826" class="ember-view reader-text-block__paragraph">We met at Entrepreneur First, which is a three-month programme with global cohorts in places like Berlin, London, San Francisco, and Singapore. It brings together technical and non-technical people to build startups. About 200 people join each cohort, and I met Alan in London.</p>
<p id="ember827" class="ember-view reader-text-block__paragraph">If you&rsquo;ve watched <em>Love Island</em>, it&rsquo;s actually a very similar concept. There are nights on the rooftop where people sit around brainstorming and discussing ideas. In that process, everything happens so fast because you have such limited time. You might start working with someone, and realise it&rsquo;s not the right fit. If it doesn&rsquo;t feel right, you have to move on <em>immediately</em>.</p>
<p id="ember828" class="ember-view reader-text-block__paragraph">It was quite brutal, to be honest. I was working 16, 17 hours every single day (even on weekends) for three months.</p>
<h2 dir="ltr">So in that process, did you explore a few different ideas? Or did you know this was the one for you?</h2>
<p id="ember831" class="ember-view reader-text-block__paragraph">Each co-founder brings a distinct area of expertise. My background is in Computer Science (I did my master&rsquo;s in Machine Learning) so I can pretty much build anything in any space. Alan had expertise in financial management and we had both worked with a few different people before we teamed up. We both brought significant entrepreneurial experience to the table. I&rsquo;m a third time founder; I'd exited two startups prior to this. And Alan had sold his financial firm as well.</p>
<p id="ember832" class="ember-view reader-text-block__paragraph">They say you should invest in the founder rather than the idea, because the idea can always pivot. It involved asking a lot of uncomfortable questions, so you know that you&rsquo;re prepared to tackle anything together. That&rsquo;s what happened, and after three months, Alan was the co-founder I ended up with!</p>
<h2 dir="ltr">Wow, that sounds exciting! Was it a tough application process to get onto the programme?</h2>
<p id="ember834" class="ember-view reader-text-block__paragraph">Yes, it&rsquo;s pretty tough &ndash; they only accept 3% of applications worldwide. It&rsquo;s an intense process with three rounds of interviews where they assess your ability, mindset, and how quickly you solve problems. If the average person takes three months to solve a problem, how can you solve it faster?</p>
<p id="ember835" class="ember-view reader-text-block__paragraph">They want you to have a founder mindset coming into the programme. Throughout my life, I always ask, <em>what&rsquo;s the quickest way to do this?</em> because I&rsquo;m a bit lazy. I always want to find the quickest solution, and that mindset really helps.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/e8f14fb4-f534-49df-b92e-c0ec1692a6de" alt="" width="533" height="400"></p>
<h2 class="ember-view reader-text-block__paragraph">Is there something most people misunderstand about AI?</h2>
<p id="ember838" class="ember-view reader-text-block__paragraph">One of the biggest problems is fear. We found that older professionals have more barriers than young people. They think: <em>I&rsquo;ve been doing this job for 20 years and AI is going to come in and take over my job.</em></p>
<p id="ember839" class="ember-view reader-text-block__paragraph">But AI is not here to replace people; it&rsquo;s here to aid you in doing your job in a more productive way. If you&rsquo;re currently spending eight hours writing a report, AI can generate the bulk of it in five-to-ten minutes, freeing you up to do something else. The real challenge is shifting perspectives away from the fear that AI is taking over the world.</p>
<h2 dir="ltr">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h2>
<p id="ember841" class="ember-view reader-text-block__paragraph">One of the hardest challenges we&rsquo;ve solved &ndash; something that our competitors still struggle with &ndash; is perfecting the feedback loop while simultaneously reducing hallucinations and maintaining creative capabilities.</p>
<p id="ember842" class="ember-view reader-text-block__paragraph">Think of it like ChatGPT generating a report. You might have to keep inputting further prompts to get it right. We've built a system that learns from those edits automatically. After editing five or so reports, that sixth report will be exactly what you want it to be, the way <em>you</em> would write it. Striking that balance of personalisation, accuracy, and controlled creativity is one of the hardest things to crack in AI, but we&rsquo;ve made major progress.</p>
<h2 dir="ltr">There&rsquo;s a lot of discussion around AI ethics. How do you ensure that your product is deployed responsibly?</h2>
<p id="ember844" class="ember-view reader-text-block__paragraph">It&rsquo;s important to set clear ethical boundaries, especially in the finance industry. That&rsquo;s why we&rsquo;ve built safeguards into our model architecture.</p>
<p id="ember845" class="ember-view reader-text-block__paragraph">For example, we train the AI to filter out inappropriate language and proactively analyse outputs against current FCA regulatory frameworks before deployment. Our <em>reasoning pipeline</em> verification process employs multiple specialised models working to validate accuracy and compliance at each step. So if a report doesn&rsquo;t meet a certain quality threshold, the system prompts a rewrite. These layered measures help to ensure compliance and trust in the technology.</p>
<h2 dir="ltr">How about scalability? What&rsquo;s been the biggest challenge in scaling your product?</h2>
<p id="ember848" class="ember-view reader-text-block__paragraph">Right now, we&rsquo;ve tapped into the UK financial and wealth management market &ndash; we&rsquo;re generating &pound;100k per month, close to &pound;1.2M ARR. But we know there&rsquo;s room for much more growth.</p>
<p id="ember849" class="ember-view reader-text-block__paragraph">Interestingly, we started out building an <em>assistant</em>, but we realised we were essentially developing a highly effective <em>report-writing tool</em>. And that&rsquo;s something that can be adapted for different industries. We&rsquo;re currently testing with various law firms, where the response has been really promising.</p>
<p id="ember850" class="ember-view reader-text-block__paragraph">Initially, we weren&rsquo;t as bold in expanding beyond finance. But that&rsquo;s changing. We&rsquo;re also scaling internationally &ndash; expanding into the US, Australia, and Canada. Of course, each market has its own regulations and nuances, but that&rsquo;s part of the challenge we&rsquo;re tackling as we grow.</p>
<h2 dir="ltr">With that in mind, have you thought about how your technology might evolve over the next 3-5 years?</h2>
<p id="ember852" class="ember-view reader-text-block__paragraph">We're building technology that will transform how financial advice works for everyday people! Within three years, our system will act like a smart virtual assistant that creates perfect reports after client meetings and also helps advisors with scheduling, follow-ups, and spotting important financial opportunities they might otherwise miss. Think of it as giving each advisor a dedicated support team, without the extra cost.</p>
<p id="ember853" class="ember-view reader-text-block__paragraph">The real excitement is in how this will make quality financial advice affordable for everyone. Today, getting personalised financial guidance often requires having significant wealth. Our technology will dramatically reduce the time advisors spend on paperwork and administrative tasks, allowing them to help more people at lower costs.</p>
<p id="ember854" class="ember-view reader-text-block__paragraph">Soon, the same quality of financial planning that currently requires a six-figure portfolio will be available to teachers, nurses, and delivery drivers trying to make smart decisions with their first retirement accounts.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/33cb6f2e-ca4a-41bf-8396-e4e228ce4e12" alt="" width="400" height="400"></p>
<h2 class="ember-view reader-text-block__paragraph">Do you see it transforming into a self-serve tool that doesn&rsquo;t involve financial advisors?</h2>
<p id="ember857" class="ember-view reader-text-block__paragraph">Yes and no. Think of it like a gym &ndash; you can use the equipment and train yourself (self-serve), but you also have the option to hire a personal trainer (financial advisor). So, it's a hybrid system, not an either-or choice.</p>
<p id="ember858" class="ember-view reader-text-block__paragraph">Many clients will gravitate toward self-serve digital tools for basic financial tasks and education, while advisors will likely focus on providing higher-value services like complex planning, behavioural coaching, and relationship management.</p>
<h2 dir="ltr">You&rsquo;ve currently got a team of 13 based in London. How have you found talent attraction?</h2>
<p id="ember860" class="ember-view reader-text-block__paragraph">One of the biggest challenges in hiring isn&rsquo;t technical skills.<em> </em>Rather, it&rsquo;s a mindset and culture fit. We need people with a startup mentality because we move fast, and some struggle with that pace.</p>
<p id="ember861" class="ember-view reader-text-block__paragraph">We&rsquo;ve created a handbook for potential new hires to give them a flavour of the startup life. But ultimately, we filter candidates early on. Our job listings are transparent and that helps to refine applications. If someone wants a standard 9-5 with great work-life balance, this isn&rsquo;t the place for them.</p>
<p id="ember862" class="ember-view reader-text-block__paragraph">The second filter is our coding test. It&rsquo;s tough, but it&rsquo;s not necessarily about whether they complete it. We&rsquo;re assessing how they work under pressure: Are they coachable? Do they ask the right questions? Problem-solving is one thing, but the right attitude is what we&rsquo;re really looking for.</p>
<p id="ember863" class="ember-view reader-text-block__paragraph">We think the opportunity in this space is <em>huge</em>, but the personality has to be the right fit.</p>
<h2 dir="ltr">That sounds intense! When it comes to AI trends, what excites you, and what do you think is overhyped?</h2>
<p id="ember866" class="ember-view reader-text-block__paragraph">The idea of AI taking over the world&hellip; it&rsquo;s a bit much. There&rsquo;s a lot of talk about AI replacing software engineers, but did computers replace mathematicians? No. AI was created by humans, and humans will always have the advantage because of our ability to think and reason. You still need the creative brain around the technology to make it happen.</p>
<p id="ember867" class="ember-view reader-text-block__paragraph">AI should help people. I read that the concept of an eight-hour workday was popularised in the early 1900s &ndash; the Ford Motor Company adopted it because Henry Ford believed it was the right approach. But who says four hours isn&rsquo;t productive? If AI handles the repetitive, mundane tasks, we can focus on deeper thinking.</p>
<p id="ember868" class="ember-view reader-text-block__paragraph">It also gives people space to be better parents, better people, to be present &ndash; and that&rsquo;s something AI can&rsquo;t do.</p>
<h2 dir="ltr">If you weren&rsquo;t working on this startup, what other problem would you like to solve with AI?</h2>
<p id="ember870" class="ember-view reader-text-block__paragraph">I don&rsquo;t have just <em>one</em> single idea, I have a list! I&rsquo;m always writing them down. I believe in tech for good: AI should be used for the benefit of people, not just to make money for a small group.</p>
<p id="ember871" class="ember-view reader-text-block__paragraph">If I weren&rsquo;t doing this, I&rsquo;d love to work on something in FemTech. Workplace harassment, sexual violence &ndash; these are issues disproportionately affecting women. I watched my own mother struggle through a career filled with invisible barriers and blatant discrimination. So I&rsquo;d love to contribute to missions in that space.</p>
<p class="ember-view reader-text-block__paragraph"><img src="https://cdn.sourceflow.co.uk/__gallery/2ed22d06-7bff-4c07-94af-7e5b3abf94ac" alt="" width="400" height="400"></p>
<h2 class="ember-view reader-text-block__paragraph">That&rsquo;s amazing! Outside of AdvisoryAI, what are you into? How do you unwind?</h2>
<p id="ember874" class="ember-view reader-text-block__paragraph">On weekends, I love visiting parks. I got into birdwatching when I was very small; nature has always drawn me in. Hiking, camping&hellip; just escaping the noise and busyness of the city.</p>
<p id="ember875" class="ember-view reader-text-block__paragraph">So most weekends, you&rsquo;ll find me in the park, camera in hand, on the lookout for birds.</p>
<h2 dir="ltr">Finally, is there anything else we haven&rsquo;t covered that you&rsquo;d like to discuss?</h2>
<p id="ember877" class="ember-view reader-text-block__paragraph">I'm still fairly new to the UK and constantly learning about the culture. One thing that stands out is how vital young people are &ndash; not just as future leaders and workers, but as the next generation of <em>everything</em>.</p>
<p id="ember878" class="ember-view reader-text-block__paragraph">If we don't invest in them well, guide them, listen to them&hellip; honestly, all this innovation we're pouring ourselves into right now could end up meaning very little.</p>
<p id="ember879" class="ember-view reader-text-block__paragraph">I don't pretend to have all the answers &ndash; definitely not a parenting expert here! But I firmly believe that the world we're trying to build with technology only matters if we&rsquo;re also nurturing those who will inherit it. They're the ones who'll take what we've started and run with it in directions we can't even imagine yet.</p>
<hr>
<p class="ember-view reader-text-block__paragraph"><strong><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400"></strong></p>
<p class="ember-view reader-text-block__paragraph"><strong>📥 Roshan is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to&nbsp;</strong><a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link=""><strong>download for free now.</strong></a></p>
<p id="ember882" class="ember-view reader-text-block__paragraph"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level,</strong><strong> <a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link="">let's talk.</a></strong></p>

Building a startup is tough, but Roshan Tamil Sellvan is working smarter and harder.

Revolutionising Wealth Management: The AdvisoryAI Story with Roshan Tamil Sellvan

<h4 class="article-editor-content__paragraph"><strong>Katya Lait and her co-founder Jack officially launched nettle in January &ndash; an idea that first took shape in the summer of 2024. Now, just three months in, they are well on their way to tackling a major inefficiency in the insurance industry.</strong></h4>
<p class="article-editor-content__paragraph">Risk engineers were spending 90% of their time buried in analysis and report writing. <strong>nettle </strong>is flipping that ratio, significantly cutting the time spent on reports and giving risk engineers back the time to do what they do best.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We spoke with Katya to hear how nettle came to life, the challenges they&rsquo;ve solved so far, and what&rsquo;s next on their startup journey.</p>
<hr>
<h2 dir="ltr">Let&rsquo;s talk about nettle! What specific problem are you solving?</h2>
<p class="article-editor-content__paragraph">In short, we&rsquo;re making the commercial insurance market more efficient. Everything from an oil rig to a fleet of company cars can be insured but, in order for the policies to be written, these assets need to first be assessed. These assessments are carried out by professionals called risk engineers.</p>
<p class="article-editor-content__paragraph">Risk engineers are often highly experienced and have extensive industry knowledge which makes them uniquely qualified to assess these assets. They complete the assessments in person which is perhaps the most interesting part of the job because they get to meet people, take observations, and give them suggestions to improve. Unfortunately, it's also the part of the job that takes up the least time &ndash; and it's something they'd like to go back to doing more.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">Most of their time (about 90% of the job) is spent on analysis and report writing. nettle is reducing that 90% down to 10%, making risk assessments more efficient and giving back the time to do more projects and assessments. So we&rsquo;re looking at an 80% reduction in the time spent per project. In effect, that creates four times value per risk engineer in an organisation.</p>
<h2 dir="ltr">How did the idea come about?&nbsp;</h2>
<p class="article-editor-content__paragraph">Jack and I started the business together last year; the nettle of today is the combination of work we were both doing in our respective projects. The idea for the underlying technology originated from a research project I was working on at Quantum Black, which involved researching and building their pioneering multi-agent system now referred to as AgentFlow. Our focus was on automating the writing of credit memos for big banks &ndash; a document not too dissimilar to a risk engineering report.</p>
<p class="article-editor-content__paragraph">Today's use case and the problem we tackle at nettle came from Jack, who spent six years in McKinsey working across insurance. Throughout that time, this opportunity kept coming up in strategic advisory projects for insurance enterprise clients. They wanted to grow commercial underwriting but the biggest bottleneck was this risk assessment step, which is unavoidable.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">That&rsquo;s where the idea for nettle was born, and my technical skill set complemented Jack&rsquo;s vision well. We got to ideating, talking to potential customers, and went from there!</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus"><img src="https://cdn.sourceflow.co.uk/__gallery/568fc785-3a23-4935-a8e5-1efa44819cff" alt="" width="445" height="400"></p>
<h2 class="article-editor-content__paragraph article-editor-content__has-focus">Do you find there to be any common misunderstandings about AI when talking to customers?</h2>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We typically have two kinds of conversations.</p>
<p class="article-editor-content__paragraph">The first is always the best. They get excited and start asking us, <em>&ldquo;Can it do this? Can it do that?&rdquo;</em>&nbsp; We&rsquo;ll get a list of 10&ndash;20 things they want nettle to do. It&rsquo;s great and exciting, but building the kind of features they want takes time, and we have to temper expectations a little bit in the short term. We put our users at the heart of every decision, so we prioritise the AI features that create real value and avoid adding unnecessary features just for the &lsquo;wow&rsquo; factor.</p>
<p class="article-editor-content__paragraph">The second is more difficult. They may misunderstand what's happening, so they'll think that we&rsquo;re reading all of their data, all of their personal information. They don&rsquo;t trust the system and want us to list every single source we use.</p>
<p class="article-editor-content__paragraph">For us, it&rsquo;s a balance. Obviously, we want to create trust within the product, but multi-agent systems are very complicated and dense in their workflows. We pull data from many sources and process them in complex ways, so we have to make tradeoffs between creating trust and not completely overwhelming them with what's going on in the background.</p>
<h2 dir="ltr">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h2>
<p class="article-editor-content__paragraph">This is super specific to a current client we're working with, but it's deploying an open-source model and building an entirely secure on-prem solution.&nbsp;</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We're working in a country right now that has strict data sovereignty laws, so no customer data can leave the region. This ruled out using OpenAI or other services that would&rsquo;ve made our jobs easier. Instead, we built this multi-agent system using in-house solutions, open source models, and internal GPU and cloud servers. It was definitely intense, but we got there in the end.&nbsp;</p>
<h2 dir="ltr">Wow! How long does it take to do something like that?</h2>
<p class="article-editor-content__paragraph">Thankfully, the way we built our agent system means replacing the underlying model is pretty quick. The challenge was working with a model that's not as smart and making it more robust with limited resources. It involved more sophisticated prompting and optimisation of the available context. But honestly, finding a GPU took the most time.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We couldn&rsquo;t rely on AWS, Azure, or Google, so it was all on-prem and fully in-house. But we&rsquo;ve learned a lot about how to build a safe and robust AI platform. When we work with clients in regions with more open data laws, we will be able to leverage the latest AI models while also delivering a highly secure solution.&nbsp;</p>
<h2 dir="ltr">What is the biggest challenge in bringing AI products like yours to market at scale?</h2>
<p class="article-editor-content__paragraph">Scalability isn't top of mind yet. We&rsquo;re still in our first year, building bespoke versions of nettle for clients. Year Two is when we&rsquo;ll step back, consider the ecosystem of solutions we&rsquo;ve built, and focus on scalability.&nbsp;</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">That said, some obvious steps we&rsquo;re taking in the short-term are to distribute requests across our specialised agents, reducing unnecessary calls to APIs and building generic components we know we will reuse across all our clients. As much as we can, we cache everything and have the system learn from itself &ndash; a crucial feature for our mission to close the knowledge gap in risk engineering.</p>
<h2 dir="ltr">That makes sense. What has been the biggest challenge in your startup so far?</h2>
<p class="article-editor-content__paragraph">Bringing AI to new markets! Beyond data sovereignty and creative use of open-source solutions as I&rsquo;ve mentioned, the biggest challenge has been translation.&nbsp;</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We&rsquo;re working in a country where English isn&rsquo;t spoken, so we have a pretty sophisticated AI system that reasons in English but delivers results to the user in their language. We have a very complex workflow around this, but it's pretty bulletproof at this stage. It also means that we can support this in virtually any country moving forward.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus"><img src="https://cdn.sourceflow.co.uk/__gallery/711c6398-64c5-42ee-8b9e-b8d07f8cba40" alt="" width="446" height="400"></p>
<h2 class="article-editor-content__paragraph article-editor-content__has-focus">You&rsquo;re only three months in and already doing great things! How do you see your technology evolving over the next few years?</h2>
<p class="article-editor-content__paragraph">Right now, we&rsquo;re positioned as an in-house solution for a specific function in insurance companies. For Series A and beyond, we&rsquo;re considering two directions.</p>
<p class="article-editor-content__paragraph">One is expanding into risk assessments: becoming not just a tech company, but also a service company. It&rsquo;d involve getting the most advanced hardware to do our assessments and becoming a centre of excellence on risk assessment. The other option is producing software and hardware together, bringing in drones and 3D visualisations that feed directly into our platform.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">There's a lot still to be uncovered. When we come into an organisation &ndash; one of the big three insurers, for example &ndash; it's challenging to get them to migrate from their existing solutions. Often, it's not ideal and it'll never be able to support the AI things that we can do. Instead of forcing migration, we could build an AI agent that runs alongside their current system, and controls their machines to fill in reports automatically with their existing software.</p>
<h2 dir="ltr">When it comes to AI trends, what do you find exciting?</h2>
<p class="article-editor-content__paragraph">For me, it&rsquo;s all the amazing developer tools that are coming out right now!&nbsp;</p>
<p class="article-editor-content__paragraph">I am just <em>so</em> much faster. What we&rsquo;ve achieved in the past three months is fuelled by the amount and quality of the AI tools I have at my disposal. I&rsquo;ve got an AI agent reviewing all my code, catching errors I wouldn&rsquo;t have spotted. It&rsquo;s accelerated everything and made our platform so much more secure.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">We're testing everything on the market right now. Anytime I hear about it's a new dev tool, I test it out immediately. It&rsquo;s exciting because the four of us can now do the work of 10 engineers.</p>
<h2>Which are your favourites? Any recommendations?</h2>
<p class="article-editor-content__paragraph">Oh yeah! I like Qodo &ndash; that&rsquo;s what I use to review my code. We use Granola for all our meetings: it's so helpful for us when we're doing tech overviews and onboarding people via Zoom. The obvious one is GitHub Co-Pilot&hellip; everyone's using that, it's fantastic. Cursor is also really good.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">My all-star favourite &ndash; it's not quite a dev tool, but it's one that I use about 20 times a day &ndash; is Claude. It's my thought partner during the day; I constantly have it open to ask quick questions.</p>
<h2 dir="ltr">And is there anything in the AI world that you think is overhyped?</h2>
<p class="article-editor-content__paragraph">Not overhyped per se, but I&rsquo;ve been underwhelmed by some built-in AI features in tools like Word or Notion. They&rsquo;re pushing them a lot, but I still see a bit more room for improvement there.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">I&rsquo;m also not sold on AI personal assistants that respond to emails and manage your calendar. I've heard about people who end up having their inbox full of AI talking to each other - it kind of misses the point of an email!</p>
<h2 dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/ba54ef3b-642d-4e8a-b68c-90a3da34c684" alt="" width="401" height="400"></h2>
<h2 dir="ltr">You must be incredibly busy. How do you relax outside of the work you do?</h2>
<p dir="ltr">Not a whole lot these days! I&rsquo;m obviously working a lot, but I recently got an Apple Watch, so I&rsquo;m trying to be more active when I can. The way they&rsquo;ve gamified it helps me to stay motivated.</p>
<h2 dir="ltr">Finally, if you weren't working on Nettle, what other problems would you be trying to solve with AI?</h2>
<p class="article-editor-content__paragraph">Well, this is a good opportunity to shout out another startup on the <em>Faces of AI</em> list &ndash; MAIHEM. What they&rsquo;re doing is super exciting.</p>
<p class="article-editor-content__paragraph article-editor-content__has-focus">If I wasn't working on something industry-specific, I would definitely be in the realm of dev tools and AI for tech developers. That&rsquo;s an area that&rsquo;s going to balloon like crazy and I can&rsquo;t wait to see what comes out of the space.</p>
<hr>
<p class="article-editor-content__paragraph"><strong><img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400"></strong></p>
<p class="article-editor-content__paragraph"><strong>📥 Katya is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to </strong><a class="article-editor-content__link article-editor-content__link" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" rel="noopener noreferrer"><strong>download for free now.</strong></a></p>
<p class="article-editor-content__paragraph article-editor-content__has-focus"><strong>At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, </strong><a class="article-editor-content__link article-editor-content__link" href="https://www.generativegroup.ai/contact-us/" rel="noopener noreferrer"><strong>let's talk.</strong></a></p>

Katya Lait and her co-founder Jack officially launched Nettle in January – an idea that first took shape in the summer of 2024. Now, just three months in, they are well on their way to tackling a major inefficiency in the insurance industry.

Solving Insurance’s Biggest Bottleneck: In Conversation With nettle's Katya Lait

<p dir="ltr">AI innovation should be shaped by diverse voices, bringing a range of perspectives to the technology that&rsquo;s shaping our future.&nbsp;</p>
<p dir="ltr">Whether you're an AI founder, researcher, or aspiring leader, the right networks, funding, and learning opportunities can make all the difference.&nbsp;These resources are designed to help you break barriers, build connections, and accelerate your journey in AI.</p>
<h2 dir="ltr">Funding &amp; Grants 💰&nbsp;</h2>
<p dir="ltr">Funding can make or break a business, but female founders still face an uphill battle securing it.&nbsp;</p>
<p dir="ltr">Between 2012 and 2022, UK AI companies founded by women accounted for only <a href="https://www.dimensions.ai/blog/analysis-of-dimensions-data-reveals-the-global-divides-in-artificial-intelligence-capabilities/">2.1%</a> of AI startup deals and raised just 0.3% of the total capital invested by venture capitalists. What&rsquo;s more, female-founded AI startups received six times less funding per deal on average, compared to their male-founded counterparts.</p>
<p dir="ltr">Momentum is building to change this. More initiatives are tackling these barriers, pushing for fairer access to funding. If you're looking for support, check out these women-only business funding, grants, and awards for 2025:</p>
<h4 dir="ltr"><a href="https://iuk-business-connect.org.uk/opportunities/" target="_blank" rel="noopener">Innovate UK&nbsp;</a></h4>
<p dir="ltr">Innovate UK holds several awards, with some cash prizes being reserved specifically for female founders to help accelerate their business and bridge the gender gap in entrepreneurship.&nbsp;</p>
<p dir="ltr">The Women Innovation Award offers at least 20 government-backed funding awards for female entrepreneurs across the UK each year. Entries are not currently open but other <a href="https://iuk-business-connect.org.uk/opportunities/">opportunities can be found on the Innovate UK website.</a></p>
<p dir="ltr">However, women-led businesses in the tech industry can apply for the Women TechEU Award right now. 160 winners will receive a &euro;75,000 (around &pound;63,000) prize and a personalised development programme.&nbsp;</p>
<p dir="ltr"><a href="https://iuk-business-connect.org.uk/opportunities/women-techeu-call-3-january-2025/">Applications for the Women TechEU Award are open until March 17th, 2025.</a></p>
<h4 dir="ltr"><a href="https://www.astia.org/" target="_blank" rel="noopener">Astia</a></h4>
<p dir="ltr">Astia is a global pioneer dedicated to investing in women-led, diverse businesses. Open for applications year-round, it supports high-growth companies where at least one woman holds significant equity on par with her male counterparts.</p>
<p dir="ltr">Its funding process takes around 4-6 weeks. Along the way, businesses receive valuable feedback on their market opportunity, as well as access to expert connections and advice.</p>
<p dir="ltr">Astia funding is a suitable fit for startups that have already gained traction or market validation. This is generally identified as Series A or B, but applications are also welcomed from Seed companies with demonstrated traction.</p>
<p dir="ltr"><a href="https://astia.my.site.com/connect/s/raiseapplication">Apply via Astia&rsquo;s online portal.</a></p>
<h4 dir="ltr"><a href="https://femalefoundersfund.com/" target="_blank" rel="noopener">Female Founders Fund</a></h4>
<p dir="ltr">Female Founders Fund was created in 2014 with the simple belief that women will build the companies of tomorrow. Since then, they have become the leading source of institutional capital for female founders raising seed capital with over $3B in enterprise value.</p>
<p dir="ltr">They offer early-stage venture capital for women-led startups.</p>
<h4 dir="ltr"><a href="https://hatchenterprise.org/" target="_blank" rel="noopener">Hatch</a></h4>
<p dir="ltr">Hatch is a community dedicated to helping founders launch, grow, and scale their business since 2014. Their programmes are designed by founders, for founders, to break down entrepreneurship barriers and empower founders with the skills, confidence, and network needed to succeed.&nbsp;</p>
<p dir="ltr">The Hatch Accelerator Programme is designed to help female-led businesses grow 10x over 10 years with mentoring and training. Plus, their Launchpad Programme helps to develop skills in business modelling, finance, communications and marketing.</p>
<p dir="ltr">Once you&rsquo;ve completed a programme, you may become eligible to apply for a business grant through the Hatch Grant Fund.</p>
<h4 dir="ltr"><a href="https://developers.google.com/womentechmakers" target="_blank" rel="noopener">Google&rsquo;s Women Techmakers&nbsp;</a></h4>
<p dir="ltr">Women Techmakers, an initiative by Google, aims to empower women in tech by providing visibility, community, and resources. Since 2013, the community has grown to over 82,000 members.</p>
<p dir="ltr">It offers funding, mentorship programmes, and events that support women in their tech careers, with a focus on education, mentorship, and networking opportunities.&nbsp;</p>
<h2 dir="ltr">Mentorship &amp; Leadership Programmes 👩&zwj;🏫&nbsp;</h2>
<p dir="ltr">Breaking into the business world is tough, and having the right guidance can make all the difference.&nbsp;</p>
<p dir="ltr">Thankfully, more programmes are stepping up to bridge the gap - offering mentorship, leadership training, and industry connections designed to help women and underrepresented groups thrive.&nbsp;</p>
<h4 dir="ltr"><a href="http://aicompetence.org">Women in AI (WAI)&nbsp;</a></h4>
<p dir="ltr">WAI is a global network dedicated to supporting and advancing women in AI. It offers mentorship opportunities, training programmes, and events designed to help women develop their skills, connect with peers and mentors, and progress in their AI careers.</p>
<h4 dir="ltr"><a href="https://ai-4-all.org/">AI4ALL&nbsp;</a></h4>
<p dir="ltr">AI4ALL provides leadership training and mentorship opportunities designed to support underrepresented groups in AI. Their aim is to inspire and empower individuals from diverse backgrounds to pursue careers in AI by offering access to high-quality resources, mentorship, and hands-on experiences.</p>
<h4 dir="ltr"><a href="https://femalefounders.org/">Female Founders Alliance&nbsp;</a></h4>
<p dir="ltr">Female Founders Alliance is dedicated to supporting female entrepreneurs in tech and AI by providing access to resources, mentorship, and networking opportunities. Founded in 2017, their programmes focus on helping women build and scale impactful tech businesses.</p>
<h4 dir="ltr"><a href="https://rewritingthecode.org/">Rewriting the Code&nbsp;</a></h4>
<p dir="ltr">Rewriting the Code offers mentorship specifically for women in AI and engineering, focusing on guiding them through their technical careers. The initiative helps participants build professional skills, connect with mentors, and overcome barriers in traditionally male-dominated fields.&nbsp;</p>
<h4 dir="ltr"><a href="https://www.zebrasunite.org/">Zebra&rsquo;s Unite&nbsp;</a></h4>
<p dir="ltr">Zebra&rsquo;s Unite is a global community that supports diverse and ethical startups by providing resources, mentorship, and networking opportunities. It is focused on fostering inclusive, socially responsible businesses, with a strong emphasis on creating positive social and environmental impact.</p>
<h2 dir="ltr">AI Networks &amp; Communities 📢&nbsp;</h2>
<p dir="ltr">Like most industries, success in the AI world isn&rsquo;t just about technical skills - it&rsquo;s also about who you know. But for women in the field, AI spaces can often feel like a boys&rsquo; club, and finding supportive and uplifting professional communities can be a challenge.</p>
<p dir="ltr">Luckily, more spaces are emerging to connect, support, and amplify women in AI. Whether you're looking for mentorship, collaboration, or a platform to share your expertise, these networks and communities are worth exploring:</p>
<h4 dir="ltr"><a href="https://www.wiml.org/">Women in Machine Learning (WiML)&nbsp;</a></h4>
<p dir="ltr">A supportive community, dedicated to shining a spotlight on women&rsquo;s excellence in machine learning and inspiring the next generation of innovators. WiML runs yearlong mentorship programmes to help women working in AI research and machine learning give and receive advice, gain knowledge, and make connections.</p>
<h4 dir="ltr"><a href="https://www.womenwhocode.com/">Women Who Code - AI Chapter</a>&nbsp;</h4>
<p dir="ltr">Women Who Code started as a community group in 2011 by a small team of engineers, seeking connection and support in the tech industry. More than a decade later, the community consists of over 360,000 technologists across 145 countries who deeply care about building a more diverse, inclusive, and equitable industry. They provide events, mentorship, and networking for women in AI.</p>
<h4 dir="ltr"><a href="https://www.blackwomeninai.com/">Black Women in AI&nbsp;</a></h4>
<p dir="ltr">A global professional membership association dedicated to the advancement of black women in artificial intelligence. Since August 2020, they have offered networking &amp; professional development for Black women in AI.</p>
<h4 dir="ltr"><a href="https://aiethicslab.com/">AI Ethics Lab&nbsp;</a></h4>
<p dir="ltr">AI Ethics Lab became active in 2017 and offers a unique approach to integrate ethics solutions into the innovation process. This includes discussion, workshops, and collaboration on ethical AI development.</p>
<h2 dir="ltr">Learning &amp; Development 📚&nbsp;</h2>
<p dir="ltr">Staying ahead in business means constantly learning, but access to the right resources isn&rsquo;t always equal. Thankfully, more initiatives are making high-quality education and training accessible.&nbsp;</p>
<p dir="ltr">From workshops to online courses, here are some top learning and development opportunities:</p>
<h4 dir="ltr"><a href="https://course.fast.ai/">Fast.ai Practical Deep Learning Course</a></h4>
<p dir="ltr">Free AI education for all skill levels - learn how to apply deep learning and machine learning to real-world problems.</p>
<h4 dir="ltr"><a href="https://www.deeplearning.ai/courses/">DeepLearning.AI</a></h4>
<p dir="ltr">DeepLearning.AI offers a comprehensive suite of courses designed to cater to various levels of expertise in AI, machine learning, deep learning, LLMs, and more</p>
<p dir="ltr">Their courses range from short certifications to full specialisation courses.</p>
<h4 dir="ltr"><a href="https://ocw.mit.edu/courses/10-01-ethics-for-engineers-artificial-intelligence-spring-2020/">MIT OpenCourseWare: AI &amp; Ethics&nbsp;</a></h4>
<p dir="ltr">This course offers a comprehensive (and free) exploration of the ethical challenges in AI development and deployment. It covers topics such as fairness, privacy, and accountability, providing an in-depth understanding of the ethical dilemmas facing AI professionals today.&nbsp;</p>
<h4 dir="ltr"><a href="https://startup.google.com/programs/accelerator/ai-first/">AI First Accelerator&nbsp;</a></h4>
<p dir="ltr">Google&rsquo;s AI First Accelerator is a programme aimed at supporting startups that are building AI-driven solutions. It offers tailored resources, mentorship, and technical assistance to early-stage AI companies to help them develop and scale their AI technologies.</p>
<p dir="ltr">You can register your interest for future events via the website.</p>
<hr>
<p dir="ltr">The future of AI should be built by everyone, not just a select few.&nbsp;</p>
<p dir="ltr">By supporting diverse founders, fostering inclusive communities, and expanding access to funding, mentorship, and education, we can create an AI industry that truly reflects the world it serves.</p>
<p dir="ltr">Whether you're launching a startup, advancing your career, or looking to make an impact, these resources are here to help you break barriers and shape the future of AI.</p>
<p><strong id="docs-internal-guid-80908b5e-7fff-51fc-92bd-e91542262ef5">Looking for your next opportunity in data and AI? Let&rsquo;s talk:&nbsp;<a href="https://www.generativegroup.ai/contact-us/">https://www.generativegroup.ai/contact-us/</a> </strong></p>

Equitable access to resources is still one of the biggest hurdles in diversifying the AI space. That’s why we put together this extensive list, packed with funding, mentorship, and learning opportunities designed to help women and underrepresented groups break barriers in AI.

AI Equal Opportunities Resources Hub 

<p>AI is evolving at an unprecedented pace. The companies leading AI innovation today are shaping the future of how we work, live, and interact with technology. By pushing boundaries, these pioneers are driving economic growth, enabling smarter decision-making, and changing the world as we know it by creating solutions that were once unimaginable.&nbsp;<br>&nbsp;<br>But who are they?<br>&nbsp;<br>In our latest report, we spotlight the 54 most exciting AI startups making an impact in the UK in 2025 - and the visionary founders leading the charge.&nbsp;<br>&nbsp;<br>These are the AI companies:<br>&nbsp;<br>✅ Securing major investment<br>✅ Gaining market traction<br>✅ Applying AI in interesting, creative, and progressive ways to solve real-world challenges.<br>&nbsp;<br>If you want to understand where AI is heading, this report gives you an insider&rsquo;s look at the pioneers redefining industries and setting new technological standards.<br>&nbsp;<br>Fill in the form below to download your free copy now and discover the companies shaping the next wave of AI innovation.</p>

<p><span data-teams="true"><strong>Meet The UK's 54 Leading Tech Founders In AI. Discover Who's Driving AI Innovation In 2025.</strong></span></p>

<p><span data-teams="true"><strong>Faces of AI - 2025</strong></span></p>

<p>AI is evolving at an unprecedented pace. The companies leading AI innovation today and their technical leaders are shaping the future of how we work, live, and interact with technology. By pushing boundaries, these pioneers are driving economic growth, enabling smarter decision-making, and changing the world as we know it by creating solutions that were once unimaginable.</p>
<p>Our Faces of AI - 2025 report features profiles for the 54 most innovative technical founders &amp; co-founders making waves in the UK AI scene, and the companies they're leading.<br>&nbsp;<br><strong>Ready to see who's driving AI forward? </strong>Fill in the form below to download your free copy now and discover the companies shaping the next wave of AI innovation.</p>

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The future of AI is being built right now. Are you paying attention?

The UK's most exciting tech founders - The leaders developing revolutionary AI systems in 2025

Key AI industry trends - The emerging AI applications shaping the future.

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Unique use cases & impact - How AI is being used to solve critical challenges across sectors.

Generative Group's Faces of AI - 2025 Report

<p dir="ltr">Forbes recently reported <a href="https://www.forbes.com/advisor/business/ai-statistics/#:~:text=72%25%20of%20businesses%20have%20adopted,at%20least%20one%20business%20function." target="_blank" rel="noopener">72% of businesses have adopted AI</a> for one or more business functions, despite the uptick in AI usage in workplaces, the majority of companies leveraging AI in their business do not have ethical guidelines, or frameworks for AI use in the workplace.&nbsp;</p>
<p dir="ltr">Without firm guidelines and frameworks for how AI is used in the workplace, companies run the risk of inadvertently creating biased outcomes, or violating employee privacy. The lack of clear structures for AI use in the workplace can create a culture of uncertainty and unregulated decision making that stifles innovation, damages employee trust, and may have negative consequences for a firm&rsquo;s reputation.</p>
<p dir="ltr">When leveraging AI, your business needs a complete approach to ethical AI implementation, which has frameworks for everything from bias mitigation to AI governance. Read on to find practical steps and strategies to make your AI systems work with ethical principles while creating business value.</p>
<h2 dir="ltr">Understanding Ethical AI in the Workplace</h2>
<p dir="ltr">Creating internal guidelines for how AI is used by your teams will present various unique challenges that your organisation must handle with care, as your leaders will need to create clear and comprehensive frameworks for how your teams use AI for each function. AI usage policies should&nbsp; be strict enough to ensure that AI systems are always used responsibly, while also ensuring that your guidelines aren&rsquo;t so strict that they hinder AI adoption or discourage employees from using AI systems..</p>
<p dir="ltr">Here are the main ethical concerns you should think about, with how your company uses AI.:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Data Privacy and Security: AI models need huge amounts of personal data, which raises questions about data collection, processing, and storage, especially when used on customer or employee datasets..</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Bias Prevention: Biased training data and teams can make AI systems carry forward existing biases that might lead to unfair outcomes for certain groups of people..</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Transparency: AI tools often work like "black boxes&rdquo;, where users can&rsquo;t see the workings between input and output, which can cause transparency issues with how outputs and decisions are made.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Accountability: Often there is minimal accountability in businesses for the decisions made by AI, making it tough to figure out who in an organisation is&nbsp; responsible for any negative outcomes.</p>
</li>
</ul>
<p dir="ltr">A reliable governance structure helps deal with these challenges. Right now, most countries do not have comprehensive regulations for how AI should be used, leaving businesses to self regulate their AI usage. While some countries and states do have some basic guidelines and regulations in place, these are often not comprehensive enough to ensure positive outcomes from AI usage across the board.</p>
<p dir="ltr">Creating ethical AI systems needs skilled people who grasp both technical details and ethical implications, which is where companies like Generative can help, as we can help your firm recruit the AI ethics specialists needed to set up governance frameworks and ethical AI usage guidelines for your firm.</p>
<h2 dir="ltr">Developing an Ethical AI Framework</h2>
<p dir="ltr">If your company uses AI systems as part of it&rsquo;s workflows, it is essential to have ethical AI guidelines and frameworks in place, your AI framework will need clear guidelines and policies that your team can follow when working with AI as part of their day to day duties,&nbsp; providing a clear structure to be followed while staying flexible enough to adapt as technologies evolve and new use cases emerge.</p>
<p dir="ltr">Before creating your internal frameworks and policies, your first step should be to undertake a complete risk assessment to review the potential ethical, legal, and social effects of your AI implementation. These components form the foundation of your framework:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Define clear AI usage boundaries and permissible applications.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Establish transparent decision-making processes.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Implement accountability measures for AI system outputs.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Create regular auditing schedules and performance metrics for AI systems.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Develop feedback mechanisms to improve AI systems &amp; usage.</p>
</li>
</ul>
<p dir="ltr">Stakeholder involvement plays a vital role in creating comprehensive AI policies, stakeholders from HR, IT, legal, and leadership teams should work together to develop policies that address their individual concerns, and covers their individual use cases.&nbsp;</p>
<p dir="ltr">The success of your frameworks will depend on regular reviews, audits, and updates; as the technology advances and your company adopts AI for new use cases; your audit schedule should reflect each system's complexity and usage frequency, to ensure that your policies keep pace with the rapid development of AI technology.</p>
<h2 dir="ltr">Mitigating Bias and Promoting Fairness</h2>
<p dir="ltr">AI systems made and used without strong ethical guidelines, can have the unintended consequence of showing discrimination based on gender, race, age, and other protected characteristics, which can inadvertently cause&nbsp; systemic bias within or lead to negative outcomes for certain groups of people.</p>
<p dir="ltr">Organisations must implement effective bias mitigation strategies:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Ensure diverse and representative training data across demographics</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Test and audit AI systems regularly for fairness metrics</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Create clear procedures to address identified biases</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Set up human oversight mechanisms for quality control</p>
</li>
</ul>
<p dir="ltr">Data diversity plays a vital role in reducing bias, as studies show that many AI solutions lack peer-reviewed evidence of performance. The focus should be on both data quantity and quality, teams building AI solutions need to ask not just "How much data?" but "What data?" to ensure real-life representation.</p>
<p dir="ltr">Curating teams with professionals from different backgrounds, will help your company to better identify potential biases that might otherwise go unnoticed, and bring about the balance required for ethical AI usage.</p>
<h2 dir="ltr">Empowering Employees in an AI-Driven Workplace</h2>
<p dir="ltr">Data from LinkedIn shows that <a href="https://www.greatplacetowork.com/resources/blog/100-best-training-workforce-ai">four in five U.S. employees</a> want more workplace AI training, and that only 38% of executives help their workforce become AI-literate, highlighting a need for internal upskilling and AI training programmes to help push the adoption of AI. <br>Your business's success with AI will largely depend on giving employees the ability to ethically utilise AI as a tool, through detailed training and support.<br><br></p>
<p dir="ltr">These benefits make an AI-powered workplace valuable:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Up-to-the-minute data analysis for better decisions</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Customised learning paths</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Simplified processes <a href="https://engageforsuccess.org/productivity/7-ways-ai-and-automation-can-enhance-employee-engagement/">saving 3.6 hours per week</a></p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Increased team efficiency and communication</p>
</li>
</ul>
<p dir="ltr">Building AI Literacy is a vital requirement for employers who want to encourage responsible AI usage in the workplace. Employers must ensure their staff has sufficient AI competency, to responsibly and ethically utilise the AI tools and systems they have access to. A good training strategy combines theory with ground applications.&nbsp;</p>
<p dir="ltr">Personalisation makes a significant difference in how employees get involved. AI analyses individual performance data to suggest career advancement paths and customise work based on employee priorities. This approach increases efficiency and keeps morale high.<br><br>Do you want to build an AI-literate workforce? <a href="https://www.generativegroup.ai/" target="_blank" rel="noopener">Generative's specialised recruiters</a> can connect you with AI experts who understand technical implementation and can help create your internal training programs.</p>
<p dir="ltr">A balanced approach to ethical AI usage in the workplace needs clear governance, bias prevention, and thorough staff training all spearheaded by company leaders at all levels. By creating these guidelines, your organisation can deal with privacy issues, keep processes transparent, and hold teams accountable when AI is being used in your company&rsquo;s day-to-day operations.</p>
<p>&nbsp;</p>

Forbes recently reported 72% of businesses have adopted AI for one or more business functions, despite the uptick in AI usage in workplaces, the majority of companies leveraging AI in their business do not have ethical guidelines, or frameworks for AI use in the workplace. 

Ethical AI: Navigating Ethical Use of AI in the Workplace

<p dir="ltr">AI adoption in workplaces has skyrocketed over the past few years, with <a href="https://www.forbes.com/advisor/business/ai-statistics/#:~:text=72%25%20of%20businesses%20have%20adopted,at%20least%20one%20business%20function.">72% of businesses in 2024</a> using AI systems in their workflows, despite this growth in workplace usage, there is a large knowledge gap around AI in most businesses using AI, <a href="https://hbr.org/2024/05/research-what-companies-dont-know-about-how-workers-use-ai">a recent study</a> 53% of workers feel unprepared to work with AI, saying they need more training; and close to half (44%) of business leaders don&rsquo;t know how their teams are using AI .</p>
<p dir="ltr">Tech team leaders, both in the businesses developing AI systems, and those using AI systems face a crucial challenge, balancing the promotion of responsible AI use and keeping systems available and valuable to users.&nbsp;</p>
<p dir="ltr">This highlights an urgent need for AI usage policies, training initiatives and security guidelines in workplaces which are implementing AI as part of their day-to-day workflows; as well as the need for teams creating AI systems to ensure that their systems have built in guardrails and comprehensive training documentation to ensure end-users interact with your systems responsibly.&nbsp;</p>
<p dir="ltr">Your top priority should focus on protecting users while maximising AI technology's benefits, whether you're developing new solutions or implementing existing systems.</p>
<p dir="ltr">Would you like to reshape your approach to AI safety and user protection? Let's discover how you can make it happen.</p>
<h2 dir="ltr">Establishing AI Safety Guidelines For Your Systems</h2>
<p dir="ltr">Organisations using AI will need to create a detailed usage framework that defines principles, policies, and procedures for AI development and deployment. Having these frameworks and policies enforced will ensure that new AI systems are somewhat standardised (making it easier for workers to understand) and provide processes workers can follow when using AI systems to ensure responsible and ethical usage.</p>
<p dir="ltr">Your AI safety framework implementation should follow these steps:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Define clear documentation guidelines</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Establish accountability mechanisms</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Set risk assessment protocols</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Implement monitoring systems</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Create feedback loops</p>
</li>
</ul>
<p dir="ltr">Continuous monitoring is a vital part of AI safety. The key performance indicators you should track include:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Model accuracy and fairness metrics</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Unexpected changes in user behaviour</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">AI model drift patterns</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">System anomalies and safety issues</p>
</li>
</ul>
<p dir="ltr">AI safety principles should be heavily considered during the development of any new AI systems, early risk identification and mitigation through adversarial training and red teaming testing will help prevent issues before they arise.</p>
<p dir="ltr">A culture of transparency from both AI developers and teams using AI systems is required for greater levels of AI adoption, giving users confidence in the outputs of systems and allowing any issues to be quickly identified. Stakeholders need clear and understandable explanations about the capabilities, limitations and processes of any AI systems their teams will be using.</p>
<p dir="ltr">When developing safeguards for new AI systems, developers must address both traditional cyber security threats and new vulnerabilities specific to AI systems. Security should remain a core requirement throughout your system's lifecycle, receiving security patches and updates and new vulnerabilities emerge. This comprehensive strategy helps your AI systems work as intended while protecting sensitive data and maintaining user trust.</p>
<h2 dir="ltr">Educating Users On Responsible AI Usage</h2>
<p dir="ltr">Responsible AI implementation depends heavily on end-users being properly educated on the AI systems they&rsquo;re using, as well as broader education on the capabilities and limitations of AI at large. Many organisation&rsquo;s internal guidelines, usage policies and training initiatives have not caught up with advances in AI technology and capabilities, this lack of structure creates major risks for privacy breaches and poor implementation.</p>
<p dir="ltr">Responsible AI use requires a detailed focus on user education. Your organisation should develop clear, available guidelines that explain your AI systems' functionality and data collection methods. A solid educational framework should cover:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Transparency on system processes</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Mitigating security risks</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Bias recognition and reporting</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Effective system utilisation</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Workplace adaptation strategies</p>
</li>
</ul>
<p dir="ltr">Your team should create user-friendly instructional documentation that can be understood by an average end-user, without simplifying the documentation so much as to reduce its accuracy or efficacy. Different training formats like webinars, tutorials, and written documentation accommodates various learning styles, making this training more accessible.&nbsp;</p>
<p dir="ltr">Note that any training or educational materials must be updated as systems and AI technologies evolve, allowing users to stay up to date with any new features, best practices, or security risks.</p>
<h2 dir="ltr">Implementing Safeguarding &amp; Protection Measures</h2>
<p dir="ltr">A strong mix of up-to-the-minute monitoring and proactive safeguards are needed to ensure that end users can use your systems responsibly and safely. Recent studies show that <a href="https://www.theguardian.com/technology/2024/feb/09/ai-safeguards-can-easily-be-broken-uk-safety-institute-finds" target="_blank" rel="noopener">simple prompting techniques can bypass AI safeguards immediately</a>, which can present a variety of security, ethical and in some cases even legal issues, highlighting the need for detailed and up-to-date protection measures to be put in place.</p>
<p dir="ltr">Up-to-the-Minute Monitoring Implementation Continuous monitoring systems that track data and system activities as they happen form your first line of defence, identifying any drastic changes in user behaviour or outputs, helping teams to quickly identify exploits, system errors and security risks, preventing&nbsp; bigger problems before they start and enabling swift action against potential threats.</p>
<p dir="ltr">Key monitoring points include:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Data integrity across systems</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">User access patterns and authentication</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Anomaly detection and alerts</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">System performance metrics</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Security breach attempts</p>
</li>
</ul>
<p dir="ltr">End-to-end data protection through encryption and blockchain technology ensures your data remains unaltered during transit or at rest, which is essential for preventing security breaches like data leaks. Monitoring-based restrictions help developers respond effectively to original cases of misuse, and automated tools like input and output classifiers can screen for potential violations.</p>
<p dir="ltr">Note that specialists should regularly test your protection measures through "red-teaming" exercises by attempting to breach your system's safeguards, this proactive approach helps identify and patch out any vulnerabilities before malicious actors can exploit them.</p>
<h2 dir="ltr">Ensuring Continued Improvements</h2>
<p dir="ltr">AI safety's landscape keeps changing, which makes ongoing improvements crucial to maintain reliable protection measures, very few AI applications remain static as data and problem characteristics change over time.</p>
<p dir="ltr">Implementing Active Learning AI systems should actively seek areas where human expertise can boost performance. Research shows that models explicitly designed with active learning can optimise performance through targeted human feedback. This approach lets your team:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Monitor model degradation patterns</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Identify areas requiring expert input</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Track performance metrics</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Assess security vulnerabilities</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Review user interaction patterns</p>
</li>
</ul>
<p dir="ltr">Continuous Assessment Framework Instead of treating AI as a finished product, call it a service that grows and improves over time, continuous monitoring and targeted active learning work better than resource-intensive batch assessments, this approach creates models that stay current while engaging your workforce more effectively with the problem space.</p>
<p dir="ltr">Your improvement strategy must include regular security assessments and adaptation to emerging threats, the faster evolving AI world needs a proactive approach to research, development, and adaptation. Adopting state-of-the-art practices and staying informed about emerging challenges helps promote a culture that prioritises both security and responsible AI considerations.</p>
<p dir="ltr">Responsible AI implementation needs your active commitment to user protection and education. A tech team leader's role goes beyond developing powerful AI systems, you need to create complete safety frameworks, educational documentation, and resilient protection measures.</p>
<p dir="ltr">Clear documentation, continuous monitoring, and regular security assessments form the foundation of strong AI governance. These elements work together with user-focused educational resources and feedback systems to create an environment where AI technology can thrive safely and ethically.</p>

AI adoption in workplaces has skyrocketed over the past few years, with 72% of businesses in 2024 using AI systems in their workflows, despite this growth in workplace usage, there is a large knowledge gap around AI in most businesses using AI, 

Educate and Protect: How to Promote Responsible AI Use Effectively

<p dir="ltr">Like any emerging technology, AI brings with it a unique set of challenges. While it sparks optimism for the possibilities ahead, many also feel skeptical, particularly as concerns about its misuse continue to grow.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Introducing our new guide: Navigating the Ethical Concerns of Generative AI.&nbsp;</h2>
<p>&nbsp;</p>
<p dir="ltr">In this report, we outline and explore a comprehensive list of ethical concerns around the widespread adoption of AI, including:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Data Privacy</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Bias in AI Systems</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Transparency &amp; Explainability</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Environmental Impact</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Accountability &amp; Accuracy</p>
</li>
</ul>
<p dir="ltr">For each of these concerns, you&rsquo;ll recieve practical guidance and actionable steps to help your team bridge any knowledge gaps. Navigating the fine line between innovation and ethical responsibility can be tough, but don't let this stand in the way of achieving your AI goals!</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Why You Need This Report</h2>
<p>If you&rsquo;re developing AI, you must address ethics for your systems&nbsp;to be successful. Throughout this report, we&rsquo;ve highlighted&nbsp;some of the key steps organisations can take to create AI&nbsp;systems that are fair, transparent, and responsible.</p>
<p>Fill out the form below to download "Navigating the Ethical Concerns of Generative AI" and start building your AI Ethics &amp; Data Governance dream team today.</p>
<p dir="ltr">&nbsp;</p>

<h4><strong id="docs-internal-guid-f2d2d3af-7fff-5e17-4fc7-71dc90484bcd">As AI advances faster than legislation can keep up, developers face a pivotal challenge to drive innovation, while ensuring their systems are ethical.</strong></h4>

<h1>Navigating the Ethical Concerns of Generative AI</h1>

<p>AI's rapid advancement offers unprecedented opportunities - but also serious ethical challenges. This whitepaper equips you with actionable strategies to navigate these challenges while creating fair, impactful, and responsible AI solutions. Whether you&rsquo;re scaling a startup or innovating within an enterprise, this guide is essential for building ethical AI systems.</p>
<p><strong>Ready to take action?</strong> Fill out the form below to download <strong>"Navigating the Ethical Concerns of Generative AI."</strong></p>

If you’re developing AI, you must address ethics for your tech to be a success. Throughout this report, we highlight the key steps organisations can take to create AI systems that are fair, transparent, and responsible.

Understand the critical concerns around data privacy, bias, transparency, and environmental impact in AI systems.

Explore practical frameworks to embed fairness and transparency from the design phase.

Discover why collaboration across disciplines and diversity is essential for responsible AI development.

Get insights into global, local, and company-level AI policies shaping the future of ethical AI.

Navigating the Ethical Concerns of Generative AI

<p dir="ltr">As artificial intelligence capabilities continue to rapidly expand, outpacing the development of new legislation and regulations, tech teams creating new AI systems face a critical challenge: determining not just what you can legally do with AI, but what you should do to keep systems in line with ethics standards. While AI systems might be capable (both practically and legally) of collecting vast amounts of user data or making autonomous decisions, the question of AI ethics extends far beyond technical capabilities and current regulations.</p>
<p dir="ltr">The gap between AI laws and ethical considerations creates a complex landscape for tech leaders, having to manage AI development in a minefield of &ldquo;grey areas&rdquo; and changing laws. Current AI regulations might allow for certain practices, but ethical implications often stretch beyond legal requirements,&nbsp; as you're operating in an environment where technical possibilities frequently outpace both legal frameworks and moral guidelines.</p>
<p dir="ltr">This guide examines the crucial intersection of legal compliance and ethical responsibility in AI development. You'll learn how to navigate gray areas where regulations are currently absent, understand the varying implications of current AI laws, and learn to implement ethical frameworks that protect both your organisation and its stakeholders now and in the future.</p>
<h2 dir="ltr">The Current AI Ethics Landscape</h2>
<p dir="ltr">The landscape of AI ethics has become increasingly complex, as governments, businesses and inter-governmental organisations like the UN develop their own guidelines, frameworks, and regulations for AI development . As a tech leader driving innovation in AI, you&rsquo;ll have to navigate this maze of ethical frameworks while building AI systems that are both innovative and responsible.</p>
<p dir="ltr">To help guide your journey, several key ethical principles have emerged with broad global consensus. These foundational elements of ethical AI include:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Beneficence &amp; Non-maleficence: Your AI systems should actively promote good, with solutions that benefit society at large,&nbsp; while also preventing harm.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Autonomy: Balance decision-making power between human oversight and AI capabilities.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Justice: Ensure fair and non-discriminatory outcomes from your AI systems.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Explicability: Maintain transparency in both technical function of AI systems and accountability for outcomes.</p>
</li>
</ul>
<p dir="ltr">When implementing these principles, you'll need to consider that AI systems can cause involuntary harm through three primary channels: misuse, questionable design, and unintended consequences - To mitigate these risks, your internal policies and procedures should prioritise ethical permissibility, fairness, public trust, and justifiability in every AI project.<br><br></p>
<p dir="ltr">The European Union has taken a leading role in establishing concrete frameworks, with the <a href="https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence" target="_blank" rel="noopener">AI Act becoming the world's first comprehensive AI law</a>, this regulatory foundation will require European AI teams to ensure your AI systems are safe, transparent, traceable, and non-discriminatory. However, remember that meeting legal requirements is just the baseline for AI development &ndash; true ethical AI development demands going beyond compliance to embrace responsible innovation, and acting as a driving force for new AI legislation.</p>
<h2 dir="ltr">Navigating "Grey Areas" In AI Laws &amp; Ethics</h2>
<p dir="ltr">When developing AI systems, you'll frequently encounter situations where legal compliance and ethical considerations don't perfectly align,&nbsp; with current regulations permitting certain actions that may be ethically objectionable, your responsibility as a developer extends beyond just complying with current laws, with a moral obligation to ensure your AI systems are ethical and a long term business goal to ensure that your systems will be compliant with future laws.</p>
<p dir="ltr">A risk-based approach to AI governance has emerged as the leading framework for navigating these grey areas, the European Union's AI Act classifies systems based on their potential risk levels, from minimal to prohibited. However, you'll need to consider that concrete instructions for independent risk classification are still under development.<br><br></p>
<p dir="ltr">To effectively navigate these uncertainties, consider these critical risk areas:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Bias and Discrimination: Your AI systems must be designed to prevent unfair treatment of individuals or groups.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Data Privacy: Ensure robust protection of personal information beyond basic compliance.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Transparency: Make your AI systems' decision-making processes clear and accountable.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Stakeholder Impact: Conduct thorough assessments of how your AI affects different communities.</p>
</li>
</ul>
<p dir="ltr">Regular monitoring and ethical reviews are crucial for maintaining alignment with both legal and ethical standards Remember that while implementing ethical AI helps build customer trust and improve brand reputation, your focus should extend beyond compliance to ensure your AI systems actively promote societal well-being. <br><br></p>
<p dir="ltr">Consider establishing cross-disciplinary teams with expertise in ethics, legal, technical, and business domains to integrate ethics throughout each phase of AI development.</p>
<h2 dir="ltr">Implementing Ethical AI Frameworks</h2>
<p dir="ltr">Building an internal ethical AI framework requires more than just good intentions, to implement effective ethical guidelines for your AI teams, you'll need to start by assessing your organisation's existing infrastructure, including data collection processes and security protocols.</p>
<p dir="ltr">Your ethical AI framework should incorporate these essential components:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Risk Assessment and Mitigation: Develop a comprehensive risk framework tailored to your systems&rsquo; use cases, that addresses privacy, fairness, transparency, and bias.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Clear Governance Structure: Establish an AI Governance Council with representatives from leadership,&nbsp; legal, compliance, and ethics teams.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Training Programs: Implement organisation-wide training on ethical AI principles and decision-making processes.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Monitoring Mechanisms: Institute regular audits and impact assessments to ensure ongoing ethical compliance.</p>
</li>
</ul>
<p dir="ltr">To ensure successful implementation, you'll need to secure leadership commitment and foster an organisational culture that values ethical responsibility at all levels of your organisation.&nbsp;</p>
<p dir="ltr">Creating awareness about ethical AI across your organisation is vital, with training programs and workshops emphasising its impact on your company's values and reputation.</p>
<p dir="ltr">Remember to establish clear KPIs and quality assurance programs to measure the effectiveness of your ethical AI strategy, your framework should explain enforcement mechanisms explicitly, as posting guidelines alone is insufficient without incorporating them into development processes.</p>
<p dir="ltr">By implementing these measures systematically, you're not just meeting compliance requirements &ndash; you're building a foundation for responsible AI development that aligns with both your organisation's values and societal expectations.</p>
<p dir="ltr">Ethical AI development demands more than meeting current legal requirements that apply to your organisation - it requires a long term commitment to responsible innovation that protects both your organisation and society at large, while current regulations provide a baseline framework to follow, your role as a tech leader extends beyond compliance into actively shaping the future of ethical AI systems.</p>
<p dir="ltr">Remember that the gap between legal compliance and ethical considerations represents both a challenge and an opportunity. Making ethical choices today, even in areas without clear regulations, builds lasting trust with stakeholders and creates a foundation for sustainable AI development.</p>
<p>&nbsp;</p>

As artificial intelligence capabilities continue to rapidly expand, outpacing the development of new legislation and regulations, tech teams creating new AI systems face a critical challenge: determining not just what you can legally do with AI, but what you should do to keep systems in line with ethics standards. 

AI Ethics: What is Legal vs. What is Morally Right

<p>AI World Congress has announced this years keynote and speakers including AWS, Oracle, WPP, SingTel and many more.</p>
<p>Find out more by visiting&nbsp;<a href="https://aiconference.london/">aiconference.london</a></p>

AI World Congress

<p>AI is revolutionising the enterprise. Hear from those transforming organisations through the business application of artificial intelligence.</p>
<p>The <a href="https://aibusinessconference.co.uk/">AI in Business Conference</a> welcomes a variety of speakers from many different industries sharing their insights on the business application of artificial intelligence. Never has it been more important to understand the impact of an enterprise technology. Hear real business insights and narrative on unlocking AI within your organisation.</p>
<p>Through keynote presentations, panel discussions, fireside chats, workshops and networking the event will inspire and inform those seeking out AI knowledge with actionable insights to be taken and new connections to be made. In addition the event will feature an exhibitor floor allowing those looking for enterprise level solutions and services to understand what is available and business ready.</p>
<p>Join us in London in November 2024 to hear from brilliant business leaders at the forefront of enterprise AI transformation and innovation.</p>
<p><a href="https://aibusinessconference.co.uk/">Register now</a></p>

AI in Business London

<p dir="ltr">The power of artificial intelligence is unparalleled. With its ability to improve efficiency, boost productivity, and enhance customer experience, AI has the potential to transform every business across every industry. However, to ensure that solutions are ethical and serve every intended user equitably, diversity within AI development teams must be prioritised.&nbsp;&nbsp;</p>
<p dir="ltr">Unfortunately, identifying and securing diverse AI talent is easier said than done. In the UK, only<a href="https://www.womenintech.co.uk/small-amount-of-women-in-stem/"> 25%</a> of STEM university graduates are women, and a mere<a href="https://www.blackhistorymonth.org.uk/article/section/stem-careers/the-urgency-of-greater-diversity-in-the-uks-stem-workforce/#:~:text=Women%20remain%20underrepresented%2C%20accounting%20for,Asian%2C%20and%20Minority%20Ethnic%20backgrounds"> 8%</a> of the STEM workforce comes from Black, Asian, and Minority Ethnic backgrounds.&nbsp;&nbsp;</p>
<p dir="ltr">Building a diverse AI team requires intentional effort at every stage of the hiring process. To uncover diverse talent, companies must look beyond traditional sourcing methods. To reassure candidates that they&rsquo;ll be respected, valued, and given the opportunity to thrive, they must also showcase their inclusivity during interviews.&nbsp;</p>
<p dir="ltr">At Generative, we recognise that diversity is important not only for ethical AI development but also for improving a product&rsquo;s competitiveness, sustainability, and customer reach. As AI recruitment specialists, we have the power to improve dire statistics and help companies tackle diversity-based issues right at the source. Under our watch, AI teams worldwide will be full of diverse backgrounds, perspectives, and experiences.&nbsp;&nbsp;&nbsp;</p>
<p dir="ltr">In this article, we&rsquo;ll explore how Generative can support your firm&rsquo;s diversity commitments, how it benefits AI development, and how we can champion diversity during our recruitment processes.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Why we believe diversity is important</h2>
<p dir="ltr">Diversity is far more than a box to tick; it&rsquo;s what makes AI systems balanced, fair, and truly innovative.&nbsp;</p>
<p dir="ltr">As diversity increases, so does the number of perspectives ready to challenge ideas, combat biases, and promote creative solutions. Diverse viewpoints drive innovation and ensure that AI models are developed to be inclusive to their core. Without diversity in their AI development teams, companies could end up producing<a href="https://techxplore.com/news/2023-08-bias-self-driving-software.html"> self-driving cars</a> that struggle to avoid dark-skinned pedestrians and<a href="http://faculty.haas.berkeley.edu/morse/research/papers/discrim.pdf"> mortgage approval tools</a> that unfairly hike up interest rates for black and Latino borrowers.&nbsp;&nbsp;</p>
<p dir="ltr">Diversity is also important to Generative because we know how challenging it is for AI firms. Companies cannot prioritise diverse candidates during the hiring process but forget about them later. They must also create an inclusive environment where diverse hires feel empowered to voice their ideas and are naturally compelled to stay committed to the business.&nbsp;</p>
<p dir="ltr">Our goal is to help forward-thinking companies build diverse teams that develop more robust, ethical AI solutions capable of equitably benefitting a broader audience.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">How diversity benefits AI development&nbsp;</h2>
<p dir="ltr">To understand the value of diversity within AI development teams, we must first understand the overwhelming risks of homogeneity.&nbsp;</p>
<p dir="ltr">Whether conscious or unconscious, biases can<a href="https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans"> easily slip into</a> AI-based solutions at<a href="https://mit-serc.pubpub.org/pub/potential-sources-of-harm-throughout-the-machine-learning-life-cycle/release/2"> any point</a> in their development. That said, with diverse development teams, companies can dramatically reduce the chances of deeply-integrated algorithmic biases.&nbsp;</p>
<p dir="ltr">AI models trained on datasets that overrepresent particular groups are prone to biases that impact real-world outcomes. Facial recognition software trained<a href="https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html"> predominantly</a> on images of white men proved to be harmful when the police<a href="https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf"> misidentified</a> people of<a href="https://www.nytimes.com/2024/06/29/technology/detroit-facial-recognition-false-arrests.html"> colour</a>. Similarly, medical AI models trained with<a href="https://www.nature.com/articles/s41586-019-1390-1.epdf"> skewed</a>, male-dominated datasets delivered<a href="https://www.nature.com/articles/s41746-023-00953-1"> inaccurate diagnoses</a> to women.&nbsp;&nbsp;</p>
<p dir="ltr">If these development teams had been more diverse, somebody would likely have raised alarm bells about the dangers of using such skewed training datasets. It&rsquo;s simple: hiring diverse talent and giving them the power to voice their opinions dramatically improves the accuracy (and hence value) of AI products.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">How Generative can improve your team&rsquo;s diversity</h2>
<p dir="ltr">At Generative, we help companies build world class AI teams. If we present our clients with a shortlist of predominantly diverse candidates (considering factors like gender, ethnicity, disability status, socioeconomic background, and industry experience), they&rsquo;ll be far more likely to make a diverse hire.&nbsp;&nbsp;</p>
<p dir="ltr">By engaging with minority networks, diversity-focused professional organisations, and education institutions (like XYZ), we can gain access to a greater number of qualified individuals from underrepresented backgrounds. Plus, we can craft job adverts using inclusive, non-gendered language to encourage diverse job-seekers to apply.&nbsp;&nbsp;&nbsp;</p>
<p dir="ltr">To further widen the talent pool, we encourage clients to keep their requirements as broad as possible and hire for skills rather than strict qualifications. Finally, we can offer clients the opportunity to eliminate unconscious bias through a blind recruitment process, in which we&rsquo;d remove all identifying details (e.g. age, gender, and ethnicity) before the face-to-face stage.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Embrace The Power of Diverse AI Teams</h2>
<p dir="ltr">Diversity and inclusion aren&rsquo;t just industry trends; they&rsquo;re tools that strategic companies use to gain a competitive edge. With a diverse AI team, you&rsquo;ll develop more inclusive products that reach a wider audience. You&rsquo;ll also improve innovation, creativity, and productivity with a vast range of perspectives that will contribute to every meeting.&nbsp;&nbsp;</p>
<p dir="ltr">At Generative, we encourage every company we work with to be strategic and understand the power of diverse teams in AI. To help them achieve this, we offer strategic hiring support that puts them one step closer to having a forward-thinking AI team that&rsquo;ll build the best products on the market.&nbsp;</p>
<p dir="ltr"><strong>To understand exactly how Generative can help your business curate world class AI teams and build more inclusive technologies, please contact our team. To learn more about why diversity should be prioritised and gain further insights into how to hire and retain diverse talent successfully, check out Generative&rsquo;s latest whitepaper: <a href="https://www.generativegroup.ai/reports/from-bias-to-balance/">From Bias to Balance: Strategies for Cultivating Diversity in AI</a>.&nbsp;</strong></p>
<p dir="ltr">&nbsp;</p>
<p>&nbsp;</p>

Unfortunately, identifying and securing diverse AI talent is easier said than done. In the UK, only 25% of STEM university graduates are women, and a mere 8% of the STEM workforce comes from Black, Asian, and Minority Ethnic backgrounds.  

How Generative can help improve diversity in AI teams

<h3><strong>Make Bias In AI Development A Thing Of The Past</strong></h3>
<p>The future of AI is driven by the teams building and developing AI, not just technology itself. But t<strong id="docs-internal-guid-f5a9a059-7fff-da41-c67d-851c49596ce0">he lack of diverse representation in AI teams has led to biased algorithms, discriminatory outcomes, and products that fail to serve all users.</strong></p>
<p>Which is why it's so important to curate diverse AI teams..</p>
<p>Explore our latest whitepaper, <strong>"From Bias to Balance: Strategies for Cultivating Diversity in AI"</strong> and learn how to:</p>
<ul>
<li>Identify issues with team composition, that could cause algorithmic bias.&nbsp;</li>
<li>Understand how diverse AI teams help to make more ethical AI systems.</li>
<li>Discover how to curate a diverse talent pool of AI specialists.</li>
<li>Shape your hiring policies to create balanced teams from all walks of life.</li>
</ul>
<h3><strong>Why You Need This Whitepaper</strong></h3>
<p>Biases in AI are far more than hypothetical concerns - they&rsquo;re real-world issues with profound implications. One of the biggest concerns is algorithmic bias, which can lead to unintended consequences and poor outcomes from AI systems.</p>
<p><strong>Ready to go from bias to balance?</strong> Fill out the form below to download "From Bias to Balance: Strategies for Cultivating Diversity in AI".</p>
<p><strong>Download the Whitepaper Now</strong></p>

<h4>The success of AI depends not only on the technology but on building diverse teams that drive ethical and inclusive innovation.</h4>

<h1>Strategies for Cultivating Diversity in AI</h1>

<p>As AI continues to evolve, it's critical to ensure that the solutions we build are ethical and serve diverse audiences. Whether you're a startup or an established company, this guide offers practical insights on how to cultivate diverse AI teams and create fairer, more impactful AI systems. Ready to get started? Fill out the form below to download <strong>"From Bias to Balance: Strategies for Cultivating Diversity in AI."</strong></p>

Diversity in AI-focused businesses is essential. The lack of diverse representation in AI teams has led to biased algorithms, discriminatory outcomes, and products that fail to serve all users. These biases often stem from teams made up of individuals with similar backgrounds and experiences, leading to a narrow perspective that goes unchallenged.

Create AI systems that are fair, accurate, and inclusive by prioritising diversity in your team.

Reduce algorithmic biases that can impact both business outcomes and user experiences.

Foster innovation by integrating diverse perspectives into your AI development process.

Prioritise diversity to enhance the effectiveness and inclusivity of your AI solutions.

And much more

Strategies for Cultivating Diversity in AI

<p dir="ltr">Generative AI has the potential to transform every industry.<a href="https://www.bcg.com/capabilities/artificial-intelligence/generative-ai"> According to BCG</a>, the industry leaders we&rsquo;ll be celebrating in five years will be those who established a clear generative AI strategy in 2024.&nbsp;&nbsp;</p>
<p dir="ltr">These AI systems use comprehensive training datasets to build complex algorithms that can create new, original content. As you don&rsquo;t need a degree to benefit from generative AI, all businesses can use this technology to improve efficiency, boost productivity, and enhance customer experience.&nbsp;&nbsp;</p>
<p dir="ltr">But, with great power comes great responsibility. As of yet, AI systems lack human-like critical thinking skills. This means they&rsquo;ll accept and learn from the data they&rsquo;re given, regardless of whether it contains bias. This could cause serious problems further down the line.&nbsp;&nbsp;</p>
<p dir="ltr">To remain ethical and develop reliable AI solutions, businesses must ensure that the teams responsible for developing such systems include people with diverse backgrounds and perspectives. This will help them create algorithms and products that do not contain bias and better serve a wider range of customers.&nbsp;</p>
<p dir="ltr">In this article, we&rsquo;ll delve into what makes diversity in AI so crucial and highlight six tactics you can use to build and maintain diversity within your AI teams.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Why diversity matters in generative AI design</h2>
<p dir="ltr">With its ability to create content, cultivate ideas, and influence key decisions, generative AI has enormous potential. However, the success of any AI system depends on the quality of the data it&rsquo;s trained on. If conscious or unconscious biases are embedded in the training data, they&rsquo;ll be reflected in the model&rsquo;s algorithm and undoubtedly influence its output.&nbsp;&nbsp;</p>
<p dir="ltr">Algorithmic biases can have highly damaging consequences. For instance, self-driving cars trained predominantly on data from light-skinned pedestrians now<a href="https://techxplore.com/news/2023-08-bias-self-driving-software.html"> struggle to identify and avoid dark-skinned pedestrians</a> at night. Similarly, AI models used to<a href="https://www.nature.com/articles/s41746-023-00953-1"> predict women&rsquo;s health outcomes</a> contain societal biases that cause diagnoses for Hispanic and Asian women to be far less accurate than for white women. If the teams responsible for developing such models had been diverse rather than<a href="https://deeperinsights.com/ai-blog/from-bias-to-balance-the-critical-role-of-diversity-in-ai"> homogeneous</a>, these potential biases could have been pinpointed earlier and may not have impacted the final product.&nbsp;</p>
<p dir="ltr">For AI to be as impactful as possible, it must serve all users with equal accuracy. The easiest way to achieve this is by involving a diverse group of people in the design process. Not only is this crucial from an ethical standpoint, but it&rsquo;s also a strategic business move. Products developed by diverse teams are more likely to reach and benefit a broader customer base.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">How to curate a diverse generative AI team&nbsp;</h2>
<p dir="ltr">Diverse AI teams aren&rsquo;t built by accident. Intentional effort is required at every stage of the recruitment process. Here are three tactics that&rsquo;ll boost your chances of success:&nbsp;&nbsp;</p>
<h3 dir="ltr">Reduce barriers in your hiring process&nbsp;</h3>
<p dir="ltr">Write job adverts that appeal to a wide range of candidates by<a href="https://gender-decoder.katmatfield.com/"> avoiding gendered language</a> and excessively specific requirements. If you work with an external recruitment partner, make sure they build your talent pipeline from diverse sources. Throughout the interview process, use unbiased recruitment tools (especially those with the power to filter applications) and cultivate a diverse interview panel to help candidates feel represented.&nbsp;&nbsp;</p>
<h3 dir="ltr">Include multi-dimensional representation. &nbsp;</h3>
<p dir="ltr">Diversity goes far beyond gender and race. Think about experiential and socioeconomic diversity, too. For instance, adding women to traditionally male-dominated tech teams or hiring individuals who have worked across different industries and geographies will encourage new ways of thinking.&nbsp;</p>
<h3 dir="ltr">Encourage interdisciplinary collaboration&nbsp;</h3>
<p dir="ltr">Involving more perspectives is always a good idea, especially when making mission-critical development decisions. Encourage your AI team to ask ethicists, sociologists, and colleagues in different departments for their opinions.&nbsp;&nbsp;</p>
<h2 dir="ltr"><br>How to champion diversity within your organisation&nbsp;</h2>
<p dir="ltr">Hiring diverse talent is pointless without an inclusive culture that values diverse employees and encourages them to stay. Here are three strategies that&rsquo;ll help you increase employee retention:&nbsp;&nbsp;</p>
<h3 dir="ltr">Start at the top</h3>
<p dir="ltr">Your leadership team sets the tone for inclusivity. If they<a href="https://diversio.com/what-role-should-leadership-teams-play-in-dei/"> lead by example</a> and visibly champion diversity and inclusive behaviour, it&rsquo;ll ripple throughout your organisation. Their actions should encourage transparency and highlight that diversity is a core value.&nbsp;</p>
<h3 dir="ltr">Educate every employee</h3>
<p dir="ltr">Give all employees the tools to contribute to your inclusive culture by offering<a href="https://www.reed.com/articles/diversity-and-inclusion-training-in-the-workplace"> mandatory training</a> about topics like unconscious bias and cultural competency. This also reinforces your diversity commitment to potential hires.&nbsp;&nbsp;</p>
<h3 dir="ltr">Enforce non-negotiable policies&nbsp;</h3>
<p dir="ltr">You must create and enforce policies that protect and support diverse hires. These might include<a href="https://www.cipd.org/globalassets/media/knowledge/knowledge-hub/tools/flexible-working-business-case_tcm18-52768.pdf"> flexible work arrangements</a> for working parents, or disabled employees, policies that guarantee fair treatment during<a href="https://www.cogentanalytics.com/knowledge-center/reporting-systems-blogs/understanding-kpis-and-proper-application-when-measuring-performance/#:~:text=An%20unbiased%20KPI%20is%20one,and%20to%20its%20individual%20operations."> performance evaluations</a>, and pre-arranged mentorship programmes that<a href="https://www.td.org/atd-blog/mentoring-programs-wont-forward-dei-without-intention"> remove the onus</a> from diverse employees to locate and contact potential mentors.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">When designing generative AI products, especially those with the potential to<a href="https://www.nature.com/articles/s41746-023-00953-1"> influence health outcomes,</a> determine which objects<a href="https://techxplore.com/news/2023-08-bias-self-driving-software.html"> self-driving cars</a> should avoid, or allocate sentences to<a href="https://theconversation.com/a-black-box-ai-system-has-been-influencing-criminal-justice-decisions-for-over-two-decades-its-time-to-open-it-up-200594"> convicted criminals</a>, it&rsquo;s crucial to ensure that<a href="https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans"> human and societal biases</a> are not embedded in the model&rsquo;s algorithm.&nbsp;&nbsp;</p>
<p dir="ltr">While this is essential from an ethical standpoint, it&rsquo;s a strategic move, too. Diverse teams are<a href="https://www.forbes.com/councils/forbesagencycouncil/2023/04/18/creating-a-diverse-and-inclusive-team-for-long-term-success/"> more likely to outperform homogeneous teams</a>, and by encompassing a wide range of perspectives, they&rsquo;re well-positioned to break into new markets and build products that accurately reflect the needs of a global, diverse customer base.&nbsp;&nbsp;</p>
<p dir="ltr"><strong>To learn more about why diversity should be prioritised and gain further insights into how to hire and retain diverse talent successfully, check out Generative&rsquo;s latest whitepaper: <a href="https://www.generativegroup.ai/reports/from-bias-to-balance/">From Bias to Balance: Strategies for Cultivating Diversity in AI</a>.&nbsp;</strong></p>
<p>&nbsp;</p>

Generative AI has the potential to transform every industry. According to BCG, the industry leaders we’ll be celebrating in five years will be those who established a clear generative AI strategy in 2024.  

The value of diversity in generative AI design

<p dir="ltr">With<a href="https://www.salesforce.com/news/stories/generative-ai-research/"> nearly 70%</a> of senior IT leaders naming generative AI a key business focus within the next 18 months, it&rsquo;s no surprise that ethical dilemmas are becoming a key topic of conversation.&nbsp;</p>
<p dir="ltr">Thanks to its ability to create original content using algorithms trained on vast datasets, generative AI is transforming almost every aspect of businesses worldwide.&nbsp;&nbsp;</p>
<p dir="ltr">This technological leap is one of the greatest in decades but could also become one of the most damaging advancements yet. The ethical challenges associated with generative AI are immense. It has the potential to generate<a href="https://www.theguardian.com/us-news/article/2024/aug/19/trump-ai-swift-harris-musk-deepfake-images"> untraceable images</a>,<a href="https://www.bbc.com/news/technology-35902104"> spread hate</a> and misinformation, and hinder sustainability efforts with the<a href="https://adasci.org/how-much-energy-do-llms-consume-unveiling-the-power-behind-ai/"> substantial carbon footprint</a> required to train and power large language models.&nbsp;</p>
<p dir="ltr">The biggest risk of all, however, is arguably how<a href="https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans"> human and societal biases have been embedded</a> in the algorithms of AI systems used to make life-changing decisions within the<a href="https://www.nature.com/articles/s41746-023-00953-1"> healthcare</a>,<a href="https://unidir.org/files/2021-12/UNIDIR_Does_Military_AI_Have_Gender.pdf"> military</a>,<a href="https://www.met.police.uk/advice/advice-and-information/fr/facial-recognition-technology/"> policing</a>, and<a href="https://theconversation.com/a-black-box-ai-system-has-been-influencing-criminal-justice-decisions-for-over-two-decades-its-time-to-open-it-up-200594"> justice</a> industries. The stakes are high, so every business investing in generative AI must do so ethically.&nbsp;&nbsp;</p>
<p dir="ltr">We&rsquo;ll explore the ethical implications of generative AI and how companies can use diversity as a strategic tool to avoid and mitigate bias.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Understanding bias in generative AI&nbsp;</h2>
<p dir="ltr">AI models are only as accurate as the data they&rsquo;re trained on. So, unless specifically identified and removed,<a href="https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans"> human and societal biases</a> can creep into these datasets and become embedded in the algorithms. Bias can be instilled at<a href="https://mit-serc.pubpub.org/pub/potential-sources-of-harm-throughout-the-machine-learning-life-cycle/release/2"> every stage</a> of an AI system&rsquo;s lifecycle, from data sourcing and preparation to model training, deployment, and evaluation. When the dataset used to train an AI model<a href="https://www.appen.com/blog/ethical-data-for-the-ai-lifecycle-data-preparation"> overweighs or underrepresents</a> a particular element, algorithmic bias occurs. This, in turn, leads to a flawed product with potentially dangerous outputs. It isn&rsquo;t a<a href="https://www.theguardian.com/technology/2019/apr/16/artificial-intelligence-lack-diversity-new-york-university-study"> technical problem</a>, it&rsquo;s a human one.&nbsp;&nbsp;</p>
<p dir="ltr">Historically,<a href="https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html"> the majority of datasets</a> used to train facial recognition AI models overrepresented white males and underrepresented women and people of colour. The resulting algorithms now identify white males with far greater accuracy than other demographics.&nbsp;&nbsp;</p>
<p dir="ltr">Further bias can arise during the data preparation phase, where<a href="https://www.appen.com/blog/ethical-data-for-the-ai-lifecycle-data-preparation"> humans are responsible</a> for labelling and annotating each piece of data. A predominantly white team may<a href="https://www.sciencedirect.com/science/article/abs/pii/S0364021302000848"> accurately annotate</a> the emotions shown on faces similar to theirs but struggle to do the same for people from different ethnicities. Additionally, the data cleaning stage is another potential source of bias, as what one analyst deems an &ldquo;irrelevant&rdquo; data point could be a critical anomaly for another.&nbsp;&nbsp;</p>
<p dir="ltr">In 2019, a<a href="https://www.washingtonpost.com/technology/2019/12/19/federal-study-confirms-racial-bias-many-facial-recognition-systems-casts-doubt-their-expanding-use/"> US federal study</a> found that facial recognition was most accurate for middle-aged white men, with Asian and African-American people misidentified 100 times more often. For darker-skinned women, the<a href="https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf"> error rate was 35%</a>. Despite such inaccuracies, these technologies are still used to<a href="https://www.nytimes.com/2024/06/29/technology/detroit-facial-recognition-false-arrests.html"> identify, arrest, and detain people</a> today.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Using diversity to mitigate bias&nbsp;&nbsp;</h2>
<p dir="ltr">The simplest way to avoid and remove bias from AI models is to involve diverse talent in the development process. Different perspectives in designing and creating AI systems can help identify issues like underrepresentation in datasets early on and remove bias at the source.&nbsp;</p>
<p dir="ltr">It&rsquo;s no secret that individuals of different genders, races, and ethnicities bring unique viewpoints to every conversation. If the teams responsible for developing facial recognition models had included more women and people of colour, the potential consequences of using a predominantly white training dataset may have been identified sooner.&nbsp;</p>
<p dir="ltr">One study found that large language models (LLMs) exhibited significant<a href="https://arxiv.org/html/2212.10678v2"> occupational gender bias</a> and automatically assigned &ldquo;he/him&rdquo; pronouns to statements about doctors and &ldquo;she/her&rdquo; pronouns to those about secretaries. Had there been greater gender diversity within the team developing these algorithms, these biases may not have found their way into the system.&nbsp;&nbsp;</p>
<p dir="ltr">Beyond gender, race, and ethnicity, experiential diversity is also important to enhance an AI team&rsquo;s problem-solving capabilities. For example, individuals who have worked across different industries and geographies may provide critical perspectives that help the business prepare a product that targets a broader range of customers in more diverse markets.&nbsp;</p>
<p dir="ltr">Moreover, investing in diversity doesn&rsquo;t simply mean hiring full-time employees from diverse backgrounds. It can also include integrating ad-hoc ethicists and sociologists during development phases to enrich the process with their expertise. By taking an interdisciplinary approach, companies can ensure that diverse perspectives are integrated throughout the AI development lifecycle, helping to mitigate bias at every step.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">How diverse teams create more ethical AI systems</h2>
<p dir="ltr">Building a diverse AI team leads to benefits that extend far beyond reducing bias. With a wider range of perspectives onboard, diverse teams are<a href="https://joshbersin.com/2015/12/why-diversity-and-inclusion-will-be-a-top-priority-for-2016/"> 1.7 times more innovative</a>, better at problem-solving, and more effective at challenging assumptions<a href="https://www.forbes.com/councils/forbesagencycouncil/2023/04/18/creating-a-diverse-and-inclusive-team-for-long-term-success/"> than homogeneous teams</a>.&nbsp;</p>
<p dir="ltr">Ultimately, AI models built by diverse, interdisciplinary teams are developed with a deeper understanding of the people they&rsquo;ll impact. As a result, they&rsquo;re inherently fairer, more accurate, and more inclusive.&nbsp;&nbsp;</p>
<p dir="ltr">For example, a diverse team developing a generative AI model for the healthcare industry could include AI specialists from various cultural backgrounds, professionals from multiple medical fields, and ethicists. Together, they can anticipate and address potential biases from the start, resulting in a product that is far more likely to serve all patients equitably, regardless of their race, gender, or socioeconomic status.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">As AI continues to evolve, one thing is clear: diversity is essential. To build models that are truly ethical and representative of the audiences they intend to serve, businesses must prioritise diversity within the teams responsible for developing them. Bias can work its way into AI systems at any stage, so it&rsquo;s vital to include a range of diverse opinions and perspectives throughout the process.&nbsp;&nbsp;</p>
<p dir="ltr"><strong>To learn more about why diversity should be prioritised and gain further insights into how to hire and retain diverse talent successfully, check out Generative&rsquo;s latest whitepaper: <a href="https://www.generativegroup.ai/reports/from-bias-to-balance/">From Bias to Balance: Strategies for Cultivating Diversity in AI</a>.&nbsp;</strong></p>
<p dir="ltr">&nbsp;</p>
<p>&nbsp;</p>

With nearly 70% of senior IT leaders naming generative AI a key business focus within the next 18 months, it’s no surprise that ethical dilemmas are becoming a key topic of conversation. 

The intersection of diversity and ethics in AI

<p dir="ltr">The Environment Agency has introduced a new citizen science initiative at Par Beach in Cornwall and Combe Martin in Devon, encouraging beachgoers to engage with AI to monitor water quality and beach conditions.&nbsp;</p>
<p dir="ltr">This 12-week trial, starting in October, aims to involve the public in gathering valuable data while keeping them informed about the state of their local environment.</p>
<p dir="ltr">At both beaches, visitors will find QR code signage prompting them to start a conversation with the Hello Lamp Post AI platform. This system will share the latest information from the Environment Agency&rsquo;s water quality monitoring efforts, but the interaction is designed to be more than just a one-way update. The agency hopes that beachgoers will contribute their own observations by answering questions about the number of people or dogs on the beach, the clarity of the water, or any signs of pollution.</p>
<p dir="ltr">The project has gained strong local support. Barbara Martin of Combe Martin Water Watch praised the agency&rsquo;s continued focus on water quality, stating, "We are proud of the 'Good' water quality rating for Combe Martin, and this AI scheme will empower both residents and visitors to report concerns directly and instantly." Similarly, Jenny Tagney from Friends of Par Beach, which participates in water quality monitoring projects, expressed excitement about the initiative. "We are really pleased to support the Environment Agency in its efforts to understand the key factors affecting Par Beach's water quality."</p>
<p dir="ltr">This AI-driven citizen science trial is expected to complement the Environment Agency&rsquo;s seasonal sampling efforts, which concluded on September 30. By maintaining an ongoing flow of data beyond the regular monitoring season, the project will help create a fuller picture of the environmental conditions at both beaches, involving the community directly in safeguarding their coastal areas.</p>
<p dir="ltr">This initiative signifies the integration of AI into environmental monitoring - one of many industries that will increasingly rely on AI expertise. To explore a range of diverse sectors where your skills can make an impact, <a href="https://www.generativegroup.ai/contact-us/">contact us today.</a><strong id="docs-internal-guid-d4c4296c-7fff-da99-24c6-c13cc426c710"></strong></p>

The Environment Agency has introduced a new citizen science initiative at Par Beach in Cornwall and Combe Martin in Devon, encouraging beachgoers to engage with AI to monitor water quality and beach conditions. 

AI Signs Set to Improve Beach Conditions in the South West of England

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<p>AI is transforming businesses to their core; from how they operate, to the products and services they offer. Executive committees are urging their enterprise technology and data leaders to exploit this powerful technology as quickly and as widely as possible.</p>
<p>The potential gains are huge, as are the risks of falling behind, as competitors race to streamline their operations and revolutionise their product offerings to a customer base with high expectations.</p>
<p>The technology C-suite must step up and deliver.</p>
<p><a href="https://events.reutersevents.com/momentum/europe?gad_source=1&amp;gclid=Cj0KCQjwwae1BhC_ARIsAK4Jfrzg8MP_Ex57p8OHoXCii39r98F7hmtZqtgpj0BBZRgPY-NT0y5GsIoaAvPJEALw_wcB">MOMENTUM AI </a>exists to help enterprise technology and data leaders understand how and where AI can improve their organisations, and equip them with the know-how to implement and scale the right solutions to improve their operations, services, and products.</p>
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Momentum AI

<p>AI applications are becoming increasingly popular among small-scale farmers in Kenya, helping them improve both crop quality and yields.</p>
<p dir="ltr">In Sorwot village, Kericho, farmer Sammy Selim uses Virtual Agronomist, an AI tool that provides fertiliser recommendations via WhatsApp. After following its advice, Selim's coffee yield rose from 2.3 to 7.3 tonnes, and he&rsquo;s hopeful for further improvement.&nbsp;</p>
<p dir="ltr">Before adopting Virtual Agronomist, Selim would apply fertiliser using what he described as &ldquo;general farmer&rsquo;s knowledge&rdquo;, using different types at different times of the year without an accuare understanding of the soil health. Now, Selim has optimised the farm&rsquo;s productivity. &ldquo;I could have wasted money,&rdquo; he says, reflecting on his previous overuse of fertiliser.</p>
<p dir="ltr">Similarly, Musau Mutisya - a farmer in Machakos county - uses PlantVillage to diagnose pests through his smartphone, avoiding the need for guesswork and inaccurate treatment. On a recent morning on his 1.5-acre farm, he stood next to a maize plant, pointing his phone&rsquo;s camera at one of the torn leaves using PlantVillage. A voice assistant identified the pest as the fall armyworm, then gave him advice on how to control it.&nbsp;</p>
<p dir="ltr">AI tools like Virtual Agronomist and PlantVillage are filling the gap left by the declining number of agricultural extension officers. Farmers now receive instant, data-driven advice on fertiliser use, soil health, and pest control - without waiting months for lab results or relying on guesswork.&nbsp;</p>
<p dir="ltr">Both tools rely on AI models trained on vast datasets&mdash;satellite data for soil properties and thousands of crop images for pest identification. Kenya&rsquo;s 1:1093 ratio of extension officers to farm households is far higher than the recommended 1:400, so digital solutions like AI are essential. &ldquo;We believe in the power of digital,&rdquo; says Enock Chikava from the Gates Foundation, which supports Virtual Agronomist.</p>
<p dir="ltr">In farming practices and beyond, AI adoption is creating demand for skilled workers in technology. As farmers increasingly use AI, the agricultural sector will need more professionals with expertise in data science, machine learning, and software development to power these innovative tools further.&nbsp;</p>
<p dir="ltr">This presents growing opportunities for AI talent in the agriculture sector, ensuring that future generations of farmers are not just users but contributors to the AI transformation. If you are ready to be a part of the future of AI, <span style="color: #b96ad9;"><a style="color: #b96ad9;" href="https://www.generativegroup.ai/contact-us/">get in touch today.</a></span></p>

AI applications are becoming increasingly popular among small-scale farmers in Kenya, helping them improve both crop quality and yields.

Kenyan Farmers Embrace AI for Productivity Boost

<p dir="ltr">A UN report is calling on governments and private companies to establish a global AI fund aimed at ensuring developing nations can harness the benefits of artificial intelligence. The fund would provide crucial access to AI models, computing power, and training programs, allowing access for countries unable to make significant investments.</p>
<p dir="ltr">The initiative is one of the key recommendations from the UN secretary-general&rsquo;s high-level advisory body on AI, which emphasises the need to avoid the same pitfalls seen with climate change&mdash;where developed nations surged ahead, leaving the global south behind.</p>
<p dir="ltr">Dame Wendy Hall, a renowned computer science professor at the University of Southampton and member of the UN advisory group, underscored the importance of action. &ldquo;We have a unique opportunity to ensure AI doesn&rsquo;t widen the gap between developed and developing nations,&rdquo; Hall said. &ldquo;If we don&rsquo;t act now to establish a global AI fund, we risk creating the same disparities we saw with climate change&mdash;where wealthier countries moved forward and others were left behind.&rdquo;</p>
<p dir="ltr">The report pushes for the creation of a shared repository of AI models and datasets to support the UN&rsquo;s sustainable development goals, such as eradicating poverty and improving global education. Additionally, it calls for the formation of an international scientific panel on AI that would publish an annual review on the technology&rsquo;s &ldquo;capabilities, opportunities, risks, and uncertainties.&rdquo;</p>
<p dir="ltr">Critically, the report warns that no global framework currently exists for AI governance, raising concerns about the potential for AI to be imposed on populations without their input. It advocates for regular intergovernmental dialogue to foster international cooperation and ensure fair governance.</p>
<p dir="ltr">AI governance has rapidly become a central issue on the international stage. Last year, leading AI companies and several nations agreed to a voluntary framework for testing advanced AI models. This month, the UK took a significant step by signing an international treaty designed to mitigate the risks of AI misuse.</p>
<p dir="ltr">The report's message is clear: leaving AI governance in the hands of a few developers or select countries would lead to a deeply inequitable situation. The UN believes it can play a vital role by hosting ongoing global discussions to help shape a balanced and inclusive future for AI.</p>
<p dir="ltr">As the technology continues to evolve, so too must our efforts to ensure its benefits are shared equitably across the globe.</p>
<p dir="ltr">If you're looking to bring change to the AI world - as a professional or company - <a href="https://www.generativegroup.ai/contact-us/">get in touch with us today.</a></p>
<p>&nbsp;</p>

A UN report is calling on governments and private companies to establish a global AI fund aimed at ensuring developing nations can harness the benefits of artificial intelligence. The fund would provide crucial access to AI models, computing power, and training programs, allowing access for countries unable to make significant investments.

UN Calls for Global AI Fund to Help Developing Nations

<h1 dir="ltr">Filling Skill Gaps: Traditional vs. Fractional Hiring</h1>
<p dir="ltr">The AI market is growing exponentially. It&rsquo;s projected to reach over <a href="https://www.trade.gov/market-intelligence/united-kingdom-artificial-intelligence-market-2023">&pound;800 billion</a> in the UK by 2025, with <a href="https://www.snaplogic.com/company/newsroom/press-releases/ai-skills-shortage-research">93%</a> of IT decision-makers already investing in AI. Companies now face a tipping point: their competitive edge depends on their ability to secure the best AI and Data talent.</p>
<p dir="ltr">However, there&rsquo;s a problem. While <a href="https://www.pluralsight.com/resource-center/ai-skills-report-2024">81%</a> of IT professionals believe they can use AI, only <a href="https://www.pluralsight.com/resource-center/ai-skills-report-2024">12%</a> possess the skills to do so effectively. According to Reuters, there is a <a href="https://www.thomsonreuters.com/en-us/posts/technology/needed-ai-skills/">50%</a> skill gap for AI-related positions, which is alarming. This discrepancy likely explains why nearly <a href="https://www.cfodive.com/news/employers-willing-to-pay-premium-for-ai-skilled-workers-aws-study/700810/?utm_source=Sailthru&amp;utm_medium=email&amp;utm_campaign=Issue:%202023-12-01%20CFO%20Dive%20%5Bissue:56942%5D&amp;utm_term=CFO%20Dive">75% of employers</a> struggle to find qualified AI candidates.</p>
<p dir="ltr">Hiring traditional full-time employees with the intention of long-term tenure has its benefits - strong team cohesion, loyalty, and deep integration, to name a few. However, traditional hiring is challenging during tough markets or when trying to fill niche roles (like AI, Data, and Machine Learning) where the talent pool is tiny.&nbsp;</p>
<p dir="ltr">Rather than sidelining projects while waiting for a full-time, qualified candidate to become available through traditional hiring channels, some businesses are changing their approach. Instead, they&rsquo;re hiring fractional AI and Data professionals on a part-time or project basis.&nbsp;</p>
<p dir="ltr">In this article, we&rsquo;ll explore the key differences between traditional and fractional hiring and outline when to use each strategy to fill specific skill gaps in your team.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Speed.</h2>
<p dir="ltr">Speed is crucial to stay ahead of the artificial intelligence curve. Most companies cannot afford to wait for the perfect full-time candidate to appear. Doing so risks delaying key projects and falling behind the competition. In addition to waiting for the right talent, traditional hiring processes often take weeks or months.&nbsp;</p>
<p dir="ltr">Hiring a long-term employee is a significant commitment, so many leaders engage candidates in multiple interviews with various stakeholders to assess whether they&rsquo;ll fit the role and company culture.&nbsp; While cultural fit remains essential for any hire, interview processes for fractional roles can be streamlined to introduce candidates to the key individuals with whom they&rsquo;ll collaborate.</p>
<p dir="ltr">Additionally, full-time hires often have lengthy notice periods, so even after securing an ideal candidate, there may be a waiting period before they can start. Once onboard, full-time hires typically require time to settle in, which is understandable given their long-term commitment to the company. In contrast, fractional employees are highly adaptable. They are adept at quickly integrating into any organisation, assessing immediate needs, and making an impact.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Cost.</h2>
<p dir="ltr">Cost is a significant challenge when hiring traditional full-time, permanent employees, especially at the leadership level. Take a Chief Technology Officer, for example. A full-time CTO might expect an annual salary of &pound;200,000 plus benefits such as bonuses and pension contributions. For a fraction of that cost, you could hire a fractional CTO on a part-time basis. If your budget allows, you could even onboard multiple fractional leaders for the same cost as one full-time employee.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Flexibility.</h2>
<p dir="ltr">If you&rsquo;ve created a positive work environment and company culture, full-time permanent hires will likely be loyal and offer long-term tenure. This is excellent for fostering strong team cohesion and deep integration but can be an additional challenge during turbulent times. Furthermore, hiring a full-time employee may not be necessary in AI and Data, where work is often project-based.</p>
<p dir="ltr">Although you could hire a full-time employee and upskill or transition them to a different department when priorities change, or their short-term goals are complete, this could significantly impact employee engagement. Companies often make full-time employees redundant when projects end due to completion, market changes, or budgeting issues. This damages their reputation and makes future hiring even more challenging.</p>
<p dir="ltr">Fractional hiring, on the other hand, offers complete flexibility and scalability. As demands fluctuate, you can easily adjust fractional employees&rsquo; working hours or contract length. This approach allows you to keep costs agile, protect employee satisfaction, and maintain your reputation in the broader market.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Skills.</h2>
<p dir="ltr">Since the COVID-19 pandemic, there&rsquo;s been an increase in the number of professionals prioritising balance and flexibility, particularly in forward-thinking sectors like AI and Data. As a result, a number of people have opted to become fractional consultants rather than full-time employees. This shift offers them flexibility and an improved work-life balance while keeping them engaged and fulfilled. By working on multiple projects with multiple companies simultaneously, they stay ahead of the curve in their personal development and remain up to date with the latest trends.</p>
<p dir="ltr">When hiring a traditional full-time employee, it&rsquo;s common to assess candidates based on their years of experience or area of expertise. In most cases, candidates - especially at the leadership level - will have worked in only a handful of companies. While longevity often indicates a loyal employee, fractional employees offer a unique advantage. Most fractional leaders have partnered with at least five to ten companies during their careers, often across various industries, sectors, and company sizes. As a result, they bring a diverse range of perspectives to your team.</p>
<p dir="ltr">By considering fractional hiring, you open the door to a much wider talent pool and increase your chances of a successful hire.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Comparative Analysis.</h2>
<p dir="ltr">Your company&rsquo;s specific needs and goals will determine whether traditional or fractional hiring is better for a particular role.</p>
<p dir="ltr">Generally, traditional hiring is preferable for long-term strategic roles that drive core business functions and require a deep organisational understanding, during ongoing projects with predictable timelines, and when budgets and timelines allow for a somewhat lengthy recruitment and integration process.</p>
<p dir="ltr">Fractional hiring, on the other hand, excels when needs are project-specific, where your team would benefit from the support of a specialist or expert that doesn&rsquo;t warrant a full-time role; when it&rsquo;s preferable to access expert skills without the financial burden of a full-time salary and benefits package; and when agility is essential for rapidly onboarding and offboarding talent in response to fluctuating demands and budget constraints.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Conclusion.</h2>
<p dir="ltr">Staying ahead of the curve is essential, particularly when building AI and Data teams in a candidate-driven market with a significant talent shortage. Traditional hiring offers long-term strategic benefits, strong team cohesion, and deep integration into company culture but can be slow, costly, and inflexible during market fluctuations.&nbsp;</p>
<p dir="ltr">Fractional hiring, in contrast, is cost-effective, flexible, and adaptable, though it requires careful management of part-time employees to ensure clear communication and effective integration.</p>
<p><strong id="docs-internal-guid-fed3d4ff-7fff-bcd7-1a87-004282e95f58"><br>Whether you&rsquo;re looking to seamlessly fill a skill gap with fractional talent or would prefer to integrate a full-time, long-term expert into your team, <a href="https://www.generativegroup.ai/contact-us/">Generative</a> can help build a tailored solution that will propel your business forward and keep your AI and Data teams ahead of the curve.</strong></p>

The AI market is growing exponentially. It’s projected to reach over £800 billion in the UK by 2025, with 93% of IT decision-makers already investing in AI. 

Filling Skill Gaps: Traditional vs. Fractional Hiring

<h1 dir="ltr">Fractional Hiring: The Next C-Suite Gamechanger?</h1>
<p dir="ltr">Artificial intelligence is transforming every industry, and businesses have two choices: get on board or fall behind. Over <a href="https://www.gartner.com/en/newsroom/press-releases/2024-06-26-gartner-poll-finds-55-percent-of-organizations-have-an-ai-board">50%</a> of companies have appointed an AI Leader to spearhead their evolution and adoption of new technologies to remain competitive. Additionally, <a href="https://www.emergingtechbrew.com/stories/2024/06/24/chief-ai-officers-future-c-suites-west-monroe-survey">40%</a> of emerging business leaders expect the number of Chief AI Officers to rise even further in the coming years.&nbsp;</p>
<p dir="ltr">While it&rsquo;s promising to see so many businesses staying ahead of the curve by investing in AI and Data teams, this trend poses a complex challenge. The pool of individuals qualified for AI and Data-related leadership roles is slim, yet demand is higher than ever. For companies to successfully secure a top-tier C-Suite leader, they must be very strategic.</p>
<p dir="ltr">Consequently, the traditional C-Suite hiring process is undergoing a significant transformation. Rather than relying on full-time, permanent leadership hires, forward-thinking companies engage fractional executives on a part-time or project basis. In fact, search requests for fractional leaders have increased by <a href="https://sifted.eu/articles/fractional-c-suite-2023">25%</a> in recent years.</p>
<p dir="ltr">Fractional hiring allows businesses to reap the benefits of top-tier leadership without the burden of a full-time salary. This approach is particularly advantageous in scenarios where a full-time commitment from an executive is not feasible or necessary. The flexibility inherent in fractional C-Suite roles enables companies to swiftly adapt to shifting market conditions and evolving strategic needs.&nbsp;</p>
<p dir="ltr">In this article, we&rsquo;ll explore five key reasons why fractional hiring is becoming a game-changing strategy for businesses seeking a strategic edge in the C-Suite.&nbsp;</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Gamechanger 1: Cost efficiency.&nbsp;</h2>
<p dir="ltr">Fractional executives offer significant cost advantages over traditional hires for many reasons. Firstly, full-time roles often come with high salaries and substantial benefits packages. For example, a Chief Technology Officer will expect an annual salary of over &pound;200,000 plus benefits, whereas a fractional CTO working one day a week might cost around &pound;40,000 per year. This model, therefore, allows businesses access to experienced executives they might otherwise be unable to afford.</p>
<p dir="ltr">Moreover, with fractional hiring, businesses could engage multiple fractional executives for the price of a single full-time C-Suite leader. This could exponentially increase the diversity of ideas, perspectives, and insights available to the company.</p>
<p dir="ltr">Fractional hiring also improves cost efficiency by drastically decreasing hiring and onboarding time. Compared to traditional C-Suite leaders, fractional leaders rarely have lengthy notice periods, accelerating the onboarding process. Additionally, fractional executives are incredibly adept at adapting to new assignments to make an impact much more quickly than their full-time counterparts.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Gamechanger 2: Diverse experience.</h2>
<p dir="ltr">Fractional executives often bring a wealth of experience from working with multiple companies across various sectors and industries. Unlike traditional executives who may have held a single C-Suite role for several years, fractional leaders have typically accumulated various diverse experiences by working with numerous organisations simultaneously.&nbsp;</p>
<p dir="ltr">This diverse background gives them broad perspectives and insights that&rsquo;ll propel any company forward. For instance, a Chief Technology Officer with experience in various technologies can offer a fresh perspective to a team dedicated solely to AI. Similarly, a Chief Financial Officer who has worked in the cryptocurrency sector might bring innovative cost-saving strategies to an AI firm, and a Chief Operating Officer with a background in fully remote companies can help a traditional firm enhance its flexibility and manage remote or hybrid teams more effectively.&nbsp;</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Gamechanger 3: Efficiency and focus.</h2>
<p dir="ltr">One concern many companies have about fractional hiring is whether an executive can effectively fulfil their responsibilities on a part-time basis. However, our experience at <a href="https://myfractional.ai/">Generative Fractional</a> highlights that fractional executives tend to focus exclusively on high-impact tasks.&nbsp;</p>
<p dir="ltr">Aware of the limited time available, fractional leaders prioritise essential tasks and delegate or eliminate less critical ones. In turn, this forces all members of the leadership team to redefine priorities, eliminate bottlenecks, and streamline decision-making processes.</p>
<p dir="ltr">By cutting out non-essential tasks, fractional C-Suite leaders have a higher level of focus on high-impact activities and can be significantly more productive. Many businesses have witnessed greater changes during a fractional executive&rsquo;s first month than they did with a traditional executive over an entire year!</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Gamechanger 4: Prestige and brand enhancement.</h2>
<p dir="ltr">Engaging high-calibre executives on a fractional basis can be used as a strategic tool to elevate a company&rsquo;s brand and market position. C-Suite leaders often come with a reputation and track record of success and can boost a company&rsquo;s credibility with stakeholders and customers by simply being onboard. Additionally, respected executives bring authority that can increase the likelihood of securing investments and partnerships that elevate the business.</p>
<p dir="ltr">Companies with a limited C-Suite budget that cannot afford a prestigious full-time can engage with one on a fractional basis and benefit from their reputation without incurring the costs of a permanent hire.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Gamechanger 5: Networking and strategic connections.</h2>
<p dir="ltr">One less tangible but equally valuable benefit of hiring a fractional executive is the expansive network they&rsquo;ll likely bring with them. These connections can open doors to new business opportunities, facilitate strategic partnerships, and expand the company&rsquo;s reach into new markets.</p>
<p dir="ltr">Leveraging these connections can be a powerful asset if you want to innovate your business or expand geographically. By hiring a fractional executive (or a few!), you can ensure that your company&rsquo;s next steps will be well-supported and successful.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Conclusion.</h2>
<p dir="ltr">Fractional hiring is undoubtedly a gamechanger for C-Suite positions. For companies aiming to stay agile and competitive in a rapidly evolving market, this strategy offers a flexible approach to executive management with lower costs, access to diverse insights, enhanced credibility, and valuable networks that&rsquo;ll propel your business towards its goals.</p>
<p dir="ltr">To explore how fractional hiring can transform your business&rsquo;s C-Suite strategy and position your company for success, get in touch with the team at <a href="https://myfractional.ai/">Generative Fractional.&nbsp;</a></p>
<p><strong id="docs-internal-guid-6aa9ba80-7fff-1465-0deb-4ff957ec8e19">&nbsp;</strong></p>

Artificial intelligence is transforming every industry, and businesses have two choices: get on board or fall behind. 

Fractional Hiring: The Next C-Suite Gamechanger?

<h1 dir="ltr">How to Integrate Fractional Talent in Your Business</h1>
<p dir="ltr">In recent years, recruiting talent in rapidly evolving fields like AI, Data Science, and Machine Learning has become increasingly challenging. The demand for specialised skills now far exceeds the availability of talent.</p>
<p dir="ltr">To combat this, many forward-thinking companies are adopting a new strategy: fractional hiring. This involves engaging highly skilled fractional individuals on a part-time or project basis. Unlike contract workers, fractional hires are integrated into the team as if they were full-time, permanent employees.&nbsp;</p>
<p dir="ltr">This approach allows companies to leverage their specialised knowledge and skills without the overhead or commitment of a full-time hire. This is particularly useful for <a href="https://www.generativegroup.ai/reports/the-power-of-fractional-hiring/">project-based roles</a> (e.g. AI Consultants, Data Scientists, and Machine Learning Engineers), as fractional contracts and working hours can be adjusted as demands and priorities fluctuate.&nbsp;</p>
<p dir="ltr">For businesses, the <a href="https://www.generativegroup.ai/reports/the-power-of-fractional-hiring/">benefits</a> are clear: access to highly skilled talent in a competitive and candidate-driven market, faster hiring with shorter notice periods, and the ability to scale commitment levels according to project needs. Not only is this a more cost-effective solution, but it also eliminates the need for reputation-damaging redundancies if and when the market evolves.</p>
<p dir="ltr">With any new hire, onboarding is a delicate dance that can potentially boost the success of the individual and the wider business. However, managing fractional employees requires a different approach than managing full-time, permanent hires. Effective onboarding and management are crucial for maximising productivity, efficiency, and employee satisfaction. In this article, we&rsquo;ll highlight five key strategies that have helped&nbsp;<a href="https://myfractional.ai/">Generative Fractional</a> clients achieve these goals.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Strategy 1: Define roles, responsibilities, and goals.&nbsp;</h2>
<p dir="ltr">While full-time employees often possess broad generalist skills and take on broad, varied roles across multiple teams and departments, fractional employees are typically hired for their unique, specific expertise and skillset. They are usually brought in to address particular projects or challenges, so it&rsquo;s crucial to relay these expectations throughout the interview and onboarding process.</p>
<p dir="ltr">Since fractional contracts can be adjusted to fit business needs, it may be strategic to leverage their expertise intensively within a relatively short timeframe. By defining their role, responsibilities, and goals from the outside (ideally before their first day), you can ensure their skills are utilised as effectively and efficiently as possible.&nbsp;&nbsp;</p>
<p dir="ltr">Furthermore, discussing, defining, and agreeing on clear and achievable goals at the start of the contract aligns expectations and makes the new hire feel valued and included. From a management perspective, these expectations also provide a benchmark for tracking progress and performance.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Strategy 2: Implement comprehensive onboarding.</h2>
<p dir="ltr">Fractional employees often spend a limited amount of time working in your organisation or do so on a part-time basis. While your traditional onboarding programme may offer sessions spanning a new hire&rsquo;s first few months, this must be adapted to suit fractional employees. When condensing material, do so strategically. Avoid removing information that helps them feel included in the company&rsquo;s mission. Their onboarding experience should feel efficient and productive, not rushed with the corners cut.&nbsp;&nbsp;</p>
<p dir="ltr">Don&rsquo;t overlook the simple aspects, either. Ensure that fractional hires have access to necessary software, tools, and logins from the start of their first day. A seamless onboarding process helps fractional employees quickly focus on high-impact work rather than spending time getting up to speed.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Strategy 3: Schedule regular communication.&nbsp;</h2>
<p dir="ltr">Fractional hires are often market-leading specialists, and a common mistake is to be so &ldquo;hands-off&rdquo; that they feel disconnected from their team and the wider workings of the business. Maintain regular and scheduled communication without resorting to micromanagement. To protect productivity, ensure that all project-related meetings have a clear agenda to ensure everyone&rsquo;s on the same page.</p>
<p dir="ltr">When managing employees working on a fractional basis, note that it&rsquo;s tough to engage in ad-hoc communication as you would with a traditional employee. Instead, schedule casual check-in calls to build rapport and gauge satisfaction. Understand how they&rsquo;re adapting to their new role and listen to any feedback that might improve their experience.</p>
<p dir="ltr">Don&rsquo;t forget that it&rsquo;s your responsibility to keep track of a fractional employee&rsquo;s working hours. Respect their boundaries, and avoid scheduling mission-critical meetings while they&rsquo;re unavailable.&nbsp;</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Strategy 4: Leverage technology.</h2>
<p dir="ltr">Use technology to streamline the management of fractional talent. Invest in project management software (e.g. <a href="https://www.teamwork.com/">Teamwork</a>) and communication platforms (e.g. <a href="https://slack.com/">Slack</a>) to track progress, set and manage expectations, and maintain engagement.&nbsp;</p>
<p dir="ltr">For remote or frequently off-site fractional employees, ensure they have the tools to communicate effectively with colleagues while staying informed about the wider business.</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Strategy 5: Encourage integration.</h2>
<p dir="ltr">Integrating fractional talent with permanent teams can be challenging, especially if they work part-time hours. Before their first day, tell your permanent employees about the fractional hire&rsquo;s role, specialisms, and goals. Encourage regular interaction between fractional and permanent employees to promote team cohesion and a more inclusive, productive environment.</p>
<p dir="ltr">There&rsquo;s also a huge opportunity for knowledge to be shared between fractional and full-time employees. Both parties offer unique skills and perspectives that, when combined, can give your business a competitive edge.&nbsp;</p>
<p><strong>&nbsp;</strong></p>
<h2 dir="ltr">Conclusion.</h2>
<p dir="ltr">Fractional hiring is a valuable technique for companies seeking to hire the best AI, Data, and Machine Learning professionals without the overhead or commitment of a full-time, permanent employee. However, effectively managing fractional talent is crucial for their success.&nbsp;</p>
<p dir="ltr">By clearly defining roles, expectations, and goals and delivering a focused onboarding programme, you can ensure that fractional employees integrate seamlessly into your business. By using regular communication and leveraging technology, you can enhance their connection to the team and project progress and maximise the benefits of hiring a skilled specialist on a fractional basis.</p>
<p dir="ltr">&nbsp;</p>
<hr>
<p><strong id="docs-internal-guid-beaa82d7-7fff-1cb8-ea27-9af24650225e"><br>To gain deeper insights into integrating fractional hiring into your talent strategy, download our comprehensive&nbsp;<a href="https://www.generativegroup.ai/reports/the-power-of-fractional-hiring/">whitepaper.</a> To stay ahead of the competition and position your business at the forefront of technological advancement, <a href="https://www.generativegroup.ai/contact-us/">get in touch today</a> to explore how <a href="https://myfractional.ai/">Generative Fractional</a> can help you strategically build top-tier AI and Data teams.</strong></p>

In recent years, recruiting talent in rapidly evolving fields like AI, Data Science, and Machine Learning has become increasingly challenging. The demand for specialised skills now far exceeds the availability of talent.

How to Integrate Fractional Talent in Your Business

<h3><strong>Find the AI Talent You Need Without the Full-Time Commitment</strong></h3>
<p>The future of AI is driven by the right people, not just technology. But in today&rsquo;s competitive market, securing top AI and Data talent can be challenging, and hiring full-time might not always be the best fit.</p>
<p>That&rsquo;s where fractional hiring comes in.</p>
<p>Explore our latest whitepaper, <strong>"The Power of Fractional Hiring: Innovative Strategies to Gain a Competitive Advantage,"</strong> and learn how to:</p>
<ul>
<li>Access top AI and Data professionals without the commitment of full-time salaries.</li>
<li>Scale your team&rsquo;s skills and capabilities while keeping your budget in check.</li>
<li>Introduce new ideas and specialised knowledge to help your business grow.</li>
<li>Shape your AI initiatives with confidence by using fractional AI Strategy Advisors.</li>
</ul>
<h3><strong>Why You Need This Whitepaper</strong></h3>
<p>In a rapidly changing AI landscape, staying adaptable is key. Whether you&rsquo;re a startup or a mid-sized company, this guide provides actionable insights on how fractional hiring can give you a competitive edge.</p>
<p><strong>Ready to get started?</strong> Fill out the form below to download "The Power of Fractional Hiring" and connect with our network of fractional AI experts for free.</p>
<p><strong>Download the Whitepaper Now</strong></p>
<p>Start building your AI dream team with the flexibility and expertise that fractional hiring offers.</p>

Fractional Whitepaper Report Form

<h4>Find the AI Talent You Need Without the Full-Time Commitment.</h4>

<h1>Discover The Power Of Fractional Hiring</h1>

<p>In a rapidly changing AI landscape, staying adaptable is key. Whether you are a startup or a mid-sized company, this guide provides actionable insights on how fractional hiring can give you a competitive edge.</p>

<p>Ready to get started? Fill out the form below to download "The Power of Fractional Hiring"</p>

Get the Report

The future of AI isn’t just about the technology—it’s about having the right people to drive innovation. But in today’s market, finding top AI and Data talent can be tough, and hiring full-time might not always be the best option.

 Access top AI and Data professionals without the commitment of full-time salaries.

Scale your team’s skills and capabilities while keeping your budget in check.

Introduce new ideas and specialised knowledge to help your business grow.

Shape your AI initiatives with confidence by using fractional AI Strategy Advisors.

And more

The Power of Fractional Hiring

<p>The education sector is on the brink of a transformation, and at the heart of this change is artificial intelligence. Recent announcements from the UK government have opened up a wealth of opportunities for tech companies to innovate and make a meaningful impact on the future of education. The Department for Education (DfE) is urging tech companies to develop AI tools that can significantly reduce teachers' workloads, making classroom life more efficient and allowing educators to focus on what truly matters&mdash;teaching.</p>
<h3>A Government-Backed Opportunity for Innovation</h3>
<p>In a move that underscores the government&rsquo;s commitment to integrating AI into education, the Department for Education (DfE) has announced a &pound;3 million investment to create a "content bank" of official teaching materials, curriculum guidance, and assessments. This resource is designed to give tech companies special access to high-quality, government-approved educational content. The goal? To train AI models that can generate accurate and reliable tools like workbooks and lesson plans tailored specifically for England&rsquo;s classrooms.</p>
<p>In addition to this, the government is offering a further &pound;1 million in a competition aimed at developing the best AI tools to reduce teacher workloads. Winning developers will be tasked with creating AI-driven solutions that assist teachers with feedback and marking tasks, with a target completion date of March 2025. This competitive opportunity not only incentivises innovation but also highlights the importance of effective, AI-powered educational tools that can genuinely ease the burdens on teachers.</p>
<h3>Why This Matters for Tech Companies</h3>
<p>For tech companies, this is more than just a chance to create a product&mdash;it&rsquo;s an opportunity to shape the future of education. The DfE&rsquo;s initiative not only provides access to valuable content but also offers a platform to showcase AI&rsquo;s potential to revolutionise how education is delivered. By developing tools that are both safe and reliable, tech companies can contribute to a more efficient, effective, and supportive educational environment.</p>
<p>Moreover, the push for AI in education aligns with broader trends in the tech industry, where AI is increasingly seen as a key driver of innovation across various sectors. The opportunity to apply AI in education not only opens up new markets but also reinforces the role of technology as a transformative force in society.</p>
<h3>The Positive Impact on Education</h3>
<p>The potential benefits of AI in education are significant. Teachers like Chris Goodall, head of digital education at the Bourne Education Trust, have already been leveraging AI to streamline lesson planning and administrative tasks. By quickly generating scaffolded activities and adapting materials for students with special needs, AI frees up valuable time for teachers to engage more directly with students.</p>
<p>This approach allows educators to focus on what they do best&mdash;teaching and providing individualised support to students&mdash;while AI handles the more repetitive tasks. This shift not only enhances the quality of education but also improves job satisfaction among teachers by reducing their workload.</p>
<h3>Looking Ahead: A Collaborative Future</h3>
<p>As AI becomes increasingly integrated into education, the collaboration between tech companies and the education sector will be crucial. The DfE&rsquo;s investment and support provide a strong foundation for tech companies to develop solutions that are not only innovative but also aligned with the needs of teachers and students.</p>
<p>For tech companies looking to make a lasting impact, this is the moment to step up. By creating AI tools that enhance the educational experience and support teachers, you can play a pivotal role in shaping the future of learning. The opportunity to drive positive change in education while expanding your business&rsquo;s reach is one that should not be missed.</p>
<h3>Conclusion</h3>
<p>The UK government's push for AI in education is more than just an initiative&mdash;it's a call to action for tech companies to innovate and lead. With the right tools, AI can revolutionise the classroom, making education more efficient and impactful. Tech companies now have the chance to be at the forefront of this transformation, developing solutions that not only reduce teacher workloads but also enhance the overall educational experience.</p>
<p>At Generative, we&rsquo;re excited about the possibilities that AI brings to the education sector and beyond. If you're a tech company looking to tap into this growing market, now is the time to invest in AI talent and start building solutions that will shape the future of education.</p>
<p><a href="https://www.generativegroup.ai/contact-us/">Get in touch</a> to learn more about how partnering with Generative can help your business.</p>

The education sector is on the brink of a transformation, and at the heart of this change is artificial intelligence. Recent announcements from the UK government have opened up a wealth of opportunities for tech companies to innovate and make a meaningful impact on the future of education. 

AI in Classrooms: £1 Million Up for Grabs to Transform Teaching Workloads

<p>In a significant move that highlights the evolving relationship between artificial intelligence and the media industry, OpenAI has announced a multi-year partnership with Cond&eacute; Nast. This deal will allow the Microsoft-backed AI startup to utilise content from some of Cond&eacute; Nast's most renowned publications, including&nbsp;The New Yorker, Vogue, GQ, Vanity Fair, and Bon App&eacute;tit.</p>
<p>This agreement marks yet another milestone for OpenAI, following similar partnerships with major media outlets like The Financial Times, Associated Press, and News Corp. Through these collaborations, OpenAI aims to incorporate high-quality journalism and content into its AI-powered tools, including ChatGPT and the experimental SearchGPT, ensuring that users have access to reliable and well-sourced information.<br><br></p>
<h3>Why This Matters for the Media and AI Industries</h3>
<p>As AI continues to reshape the landscape of news discovery and content delivery, partnerships like this are becoming increasingly crucial. OpenAI's commitment to accuracy and integrity in its AI products is evident in this deal, as the company works closely with media organisations to respect and preserve the quality of journalism.</p>
<p>Brad Lightcap, OpenAI&rsquo;s COO, emphasised the importance of this collaboration, stating, "We&rsquo;re committed to working with Cond&eacute; Nast and other news publishers to ensure that as AI plays a larger role in news discovery and delivery, it maintains accuracy, integrity, and respect for quality reporting."</p>
<p>For Cond&eacute; Nast, this partnership represents an opportunity to embrace new technologies while safeguarding the intellectual property that is the foundation of its business. Roger Lynch, CEO of Cond&eacute; Nast, highlighted the necessity of adapting to technological advancements, especially at a time when media companies are grappling with the challenges posed by the digital age.<br><br></p>
<h3>A Win-Win Partnership</h3>
<p>This partnership not only provides Cond&eacute; Nast with a new revenue stream but also ensures that its content continues to reach a broad audience through innovative AI platforms. Lynch remarked, "Our partnership with OpenAI begins to make up for some of that revenue, allowing us to continue to protect and invest in our journalism and creative endeavors."</p>
<p>OpenAI&rsquo;s approach to working with publishers has been one of transparency and collaboration, which has fostered a productive relationship with Cond&eacute; Nast. This deal underscores the potential for AI to enhance the distribution of quality content, while also supporting the sustainability of journalism in the digital era.<br><br></p>
<h3>The Bottom Line</h3>
<p>OpenAI&rsquo;s partnership with Cond&eacute; Nast highlights that AI is more than just a passing trend&mdash;it's a transformative force with lasting impact. As AI increasingly integrates into different sectors, the demand for skilled AI professionals is only set to rise. Now is the time to start building your AI team, positioning your business to harness the full potential of these advancements.</p>
<p>At Generative, we&rsquo;re ready to help you find the talent that will drive your business forward. <a href="https://www.generativegroup.ai/contact-us/">Get in touch today</a>.</p>

In a significant move that highlights the evolving relationship between artificial intelligence and the media industry, OpenAI has announced a multi-year partnership with Condé Nast. This deal will allow the Microsoft-backed AI startup to utilise content from some of Condé Nast's most renowned publications, including The New Yorker, Vogue, GQ, Vanity Fair, and Bon Appétit.

OpenAI Partners with Global Media Company Behind Vogue, GQ, and The New Yorker

<p dir="ltr">Are you looking to create a more innovative and efficient business this year? AI&rsquo;s definitely the way to go! And that&rsquo;s why it&rsquo;s more important than ever to get clued up on the hottest AI roles.&nbsp;</p>
<p dir="ltr">It&rsquo;s important to recognise that the AI job market&rsquo;s rapidly growing &ndash; and that means it&rsquo;s also becoming increasingly competitive. So, whether you&rsquo;re in HR or recruitment, or a tech company C-level exec you&rsquo;ll want to ensure your company continues to thrive, despite this additional competition.</p>
<p dir="ltr">The secret to success? It&rsquo;s making the AI talent that&rsquo;ll keep you at the forefront of your industry your priority. In this blog, we&rsquo;ll explore the current top AI roles to hire for and highlight the skillsets and expertise needed for each.&nbsp;</p>
<p dir="ltr">If you understand these roles, and how they can help your organisation, you&rsquo;ll be better placed to attract and retain the very best AI professionals.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">1. &nbsp; Machine Learning Engineer</h2>
<p dir="ltr">Machine Learning Engineers are really important in the world of AI.&nbsp; They&rsquo;re mainly focused on the development and deployment of machine learning models. In short, they&rsquo;re the architects behind the systems that can learn from data and provide us with insights.</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">Machine Learning Engineers have a range of responsibilities that ensure the seamless operation and continual improvement of machine learning models. Typical tasks might include:</p>
<ul>
<li dir="ltr"><strong>Training Models</strong>: Training machine learning models on large datasets, fine-tuning parameters, and ensuring that the models predict things accurately.</li>
<li dir="ltr"><strong>Developing Algorithms</strong>: Crafting and optimizing algorithms that can process data and learn from it is a core part of their job. This involves selecting the appropriate model architecture and features for specific tasks.</li>
<li dir="ltr"><strong>Optimising Performance</strong>: Ensuring that the models run efficiently in real-world applications. This includes reducing latency, improving accuracy, and scaling solutions.</li>
</ul>
<h2 dir="ltr">Required Skills</h2>
<p dir="ltr">If you&rsquo;re looking for a great Machine Learning Engineer, they&rsquo;ll need:</p>
<ul>
<li dir="ltr"><strong>To Be Proficient in Programming Languages</strong>: Knowing languages such as Python and R is crucial &ndash; they&rsquo;re the backbone of most machine learning projects.</li>
<li dir="ltr"><strong>Experience in ML Frameworks:</strong> Familiarity with machine learning frameworks like TensorFlow and PyTorch is vital. These kinds of tools provide the necessary infrastructure to build models efficiently.</li>
<li dir="ltr"><strong>A Strong Background in Maths:</strong> Mathematics is important and particularly areas like linear algebra, probability, and statistics, which are all necessary to grasp the underlying principles of machine learning algorithms.</li>
</ul>
<p>&nbsp;</p>
<h2 dir="ltr">2. &nbsp; Data Scientist</h2>
<p dir="ltr">Think of Data Scientists as the detectives of the AI world. They work on identifying hidden patterns and insights from large amounts of data to help us make data-driven business decisions.&nbsp;</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">Data Scientists normally focus on:</p>
<ul>
<li dir="ltr"><strong>Data Analysis:</strong> They analyse complex datasets to pick out trends, correlations, and/or anomalies that can provide valuable business insights.&nbsp;</li>
<li dir="ltr"><strong>Statistical Modelling</strong>: Creating and applying statistical models is a crucial part of a Data Scientist&rsquo;s job. They help us to predict future trends, assess risks, and simulate different scenarios so that we can plan.</li>
<li dir="ltr"><strong>Creating Data Visualisations</strong>: Data Scientists transform their findings into visual formats (think charts, graphs, and dashboards). By doing this, they make complex data accessible and understandable for everyone in an organisation.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">A good Data Scientist needs to be able to:</p>
<ul>
<li dir="ltr"><strong>Manipulate Data</strong>: Being able to manipulate and clean data is essential to ensure accuracy and consistency.</li>
<li dir="ltr"><strong>Statistical Analysis</strong>: This is necessary for developing models and interpreting complex datasets.&nbsp;</li>
<li dir="ltr"><strong>Programming</strong>: Expertise in programming languages like Python and R is vital. Languages like these are commonly used for data analysis, statistical modelling, and machine learning.</li>
<li dir="ltr"><strong>Data Visualisation Tools</strong>: Experience using data visualisation tools such as Tableau and Power BI is important. That&rsquo;s because these tools help create visual representations of data, which means better interpretation and communication across a business.</li>
</ul>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">3. &nbsp; Data Engineer</h2>
<p dir="ltr">If you want to be a data-driven organisation, Data Engineers need to be your backbone. They&rsquo;re responsible for designing and maintaining the data infrastructure, ensuring that data&rsquo;s collected, stored, and processed efficiently.</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">Data Engineers will be responsible for:</p>
<ul>
<li dir="ltr"><strong>Building Data Pipelines:</strong> Constructing and managing data pipelines that transport data to data storage systems.</li>
<li dir="ltr"><strong>The Quality of Data:</strong> Data Engineers will manage quality control, including data cleansing, validation, and monitoring to prevent problems.</li>
<li dir="ltr"><strong>Data Storage Optimisation</strong>: They&rsquo;ll design and optimise data storage solutions to ensure data can be easily and quickly accessed. They&rsquo;ll help companies select appropriate storage tech and will also configure them according to a business&rsquo; needs.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">Data Engineers should have:</p>
<ul>
<li dir="ltr"><strong>Proficiency in SQL</strong>: SQL&rsquo;s needed to manage databases. It&rsquo;s a fundamental skill for accessing and manipulating data stored in structured formats.</li>
<li dir="ltr"><strong>ETL Processes</strong>: Expertise in ETL (Extract, Transform, Load) processes is also necessary. Data Engineers need to be able to extract data and transform it into a usable format.</li>
<li dir="ltr"><strong>Big Data Technologies</strong>: Big data technologies such as Hadoop and Spark are important in enabling us to process massive datasets.</li>
<li dir="ltr"><strong>Experience in Cloud Platforms</strong>: Cloud platforms like AWS, Azure, and Google Cloud are increasingly important for Data Engineers as they&rsquo;re often used to build data infrastructure.</li>
</ul>
<p>&nbsp;</p>
<h2 dir="ltr">4. &nbsp; AI Ethics Specialist</h2>
<p dir="ltr">As AI becomes more and more popular, the role of an AI Ethics Specialist is emerging as one of the most crucial. These specialists will help an organisation to manage the complex moral landscape of AI, ensuring that the tech is designed and used responsibly, fairly, and transparently.</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">AI Ethics Specialists will:</p>
<ul>
<li dir="ltr"><strong>Develop Ethical Guidelines</strong>: One of their main tasks is to create comprehensive ethical guidelines to govern all AI development and deployment.&nbsp;</li>
<li dir="ltr"><strong>Conduct Ethical Impact Assessments</strong>: They&rsquo;ll also perform assessments to measure the ethical implications of AI systems. And identify risks such as bias, privacy concerns, and unintended consequences, before making recommendations for mitigating these risks.</li>
<li dir="ltr"><strong>Promote Responsible AI Use</strong>: AI Ethics Specialists advocate for the responsible use of AI technologies. This includes educating colleagues on ethical issues, encouraging a culture of ethical awareness, and ensuring compliance with ethical standards and regulations.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">AI Ethics Specialist will excel in:&nbsp;&nbsp;</p>
<ul>
<li dir="ltr"><strong>Ethical Frameworks Knowledge</strong>: They&rsquo;ll have a deep understanding of ethical theories and frameworks, meaning they can develop ethical guidelines and make informed decisions about any ethical issues.</li>
<li dir="ltr"><strong>Understanding AI Technologies</strong>: Familiarity with AI technologies and their applications is crucial. They&rsquo;ll understand how AI systems work, the data needed, and any ethical challenges.</li>
<li dir="ltr"><strong>Analytics</strong>: The ability to analyse and assess the ethical implications of AI systems is vital. AI Ethics Specialists must be able to identify potential risks and evaluate the impact of AI.</li>
<li dir="ltr"><strong>Communication</strong>: Strong communication skills are important for conveying complex ethical issues to a variety of audiences. AI Ethics Specialists must be able to articulate ethical concerns clearly and persuasively.</li>
</ul>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">5. &nbsp; Robotics Engineer</h2>
<p dir="ltr">Robotics Engineers are key in designing and developing advanced robotic systems that use AI to perform complex tasks. These specialists combine expertise in robotics and AI to create machines that can operate alone or assist humans.</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">Robotics Engineers&rsquo; responsibilities normally include:</p>
<ul>
<li dir="ltr"><strong>Building Robotic Prototypes:</strong> They design and construct prototypes to test and refine robotic concepts.&nbsp;</li>
<li dir="ltr"><strong>Programming Robotic Systems</strong>: These engineers write the software that controls robotic systems, enabling them to perform specific tasks.&nbsp;</li>
<li dir="ltr"><strong>Integrating AI Algorithms</strong>: A main part of their role is integrating AI algorithms into robotic systems to enhance capabilities. This can involve implementing machine learning techniques for decision-making, computer vision for object recognition, and natural language processing for human-robot interaction.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">With Robotics Engineers, look out for:&nbsp;</p>
<ul>
<li dir="ltr"><strong>Expertise in Robotics Engineering</strong>: A solid foundation in robotics engineering principles is needed. This includes knowledge of kinematics, dynamics, and control systems for the movement and behaviour of robotic systems.</li>
<li dir="ltr"><strong>Programming Skills</strong>: Proficiency in programming languages such as C++ and Python is vital. They&rsquo;re languages commonly used for developing robotic applications.</li>
<li dir="ltr"><strong>Knowledge of Control Systems</strong>: Understanding control systems is essential for designing robots that can perform precise movements and react to changes in their environment. This includes expertise in sensors, actuators, and feedback mechanisms.</li>
</ul>
<p>&nbsp;</p>
<h2 dir="ltr">6. &nbsp; Computer Vision Engineer</h2>
<p dir="ltr">Computer Vision Engineers are specialists in creating algorithms that allow machines to interpret and understand visual information from the world around them.&nbsp;</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">A Computer Vision Engineer will undertake a number of tasks to develop cutting-edge visual interpretation systems, including:</p>
<ul>
<li dir="ltr"><strong>Image and Video Processing</strong>: They work on processing images and videos to pull out information. This involves using techniques like filtering, enhancement, and transformation that will prepare visual data for analysis.</li>
<li dir="ltr"><strong>Recognition Systems</strong>: A significant part of their role is to create systems that can recognise objects, faces, and scenes.&nbsp;</li>
<li dir="ltr"><strong>Vision Algorithms:</strong> Computer Vision Engineers design and implement complex algorithms, allowing machines to interpret visual data and carry out tasks such as object detection, tracking, and segmentation.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">Computer Vision Engineers need a strong foundation in:</p>
<ul>
<li dir="ltr"><strong>Computer Vision Libraries</strong>: They&rsquo;ll need familiarity with libraries such as OpenCV and TensorFlow as these tools mean they can develop and deploy computer vision applications efficiently.</li>
<li dir="ltr"><strong>Deep Learning Techniques</strong>: An understanding of deep learning techniques is essential for building advanced recognition systems. Knowledge of neural networks, convolutional neural networks (CNNs), and other machine learning models is key.</li>
<li dir="ltr"><strong>Programming Skills</strong>: You&rsquo;ll also want them to be proficient in programming languages like Python and C++.&nbsp;</li>
</ul>
<p>&nbsp;</p>
<h2 dir="ltr">7. &nbsp; Bioinformatics Specialist</h2>
<p dir="ltr">Bioinformatics Specialists play an important role at the intersection of biology, computer science, and information technology. They&rsquo;ll use AI to analyse complex biological data to uncover insights that drive advancements in healthcare, genetics, and biotechnology.&nbsp;</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">Bioinformatics Specialists take on a variety of tasks to support and enhance biological research and breakthroughs. They may include:</p>
<ul>
<li dir="ltr"><strong>Genomic Data Analysis</strong>: Analysing genomic data allows us to identify patterns and relationships within DNA sequences. This involves using sophisticated algorithms and AI techniques to decode genetic information.</li>
<li dir="ltr"><strong>Developing Bioinformatics Tools:</strong> Professionals design and create software tools and databases that allow us to analyse and interpret biological data.&nbsp;</li>
<li dir="ltr"><strong>Collaborating with Biological Researchers:</strong> Bioinformatics Specialists work closely with biologists, geneticists, and other researchers for support with their experiments.&nbsp;</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">If you want a strong Bioinformatics Specialist for your team, skills to look out for include:&nbsp;</p>
<ul>
<li dir="ltr"><strong>Proficiency in Bioinformatics Tools</strong>: Bioinformatics software and tools such as BLAST, Bioconductor, and GATK are essential and are fundamental for analysing and managing biological data.</li>
<li dir="ltr"><strong>Knowledge of Biology and Genetics:</strong> A strong understanding of biological principles and genetic concepts is critical. This includes knowledge of molecular biology, genomics, and systems biology, which provides the context needed to interpret computational analyses.</li>
<li dir="ltr"><strong>Programming Skills</strong>: Proficiency in programming languages like Python and R is also vital as they&rsquo;re often used for developing bioinformatics algorithms, data analysis, and visualisation.</li>
</ul>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">8. &nbsp; Automation Engineer</h2>
<p dir="ltr">Want to be efficient and innovative? Automation Engineers are essential! They design and implement automated systems and processes, to streamline operations, reduce errors, and improve productivity.&nbsp;</p>
<h3 dir="ltr">Key Responsibilities</h3>
<p dir="ltr">To enhance operational efficiency, Automation Engineers will:</p>
<ul>
<li dir="ltr"><strong>Develop Automation Scripts</strong>: They write and maintain scripts to automate routine tasks and processes. They&rsquo;ll use scripting languages like Python and JavaScript to create solutions.</li>
<li dir="ltr"><strong>Optimise Workflows</strong>: Part of their role is to analyse existing workflows and identify where improvements can be made. By doing this they help organisations save time and resources and enhance overall performance.</li>
<li dir="ltr"><strong>Integrate AI Technologies</strong>: Automation Engineers incorporate AI technologies into automated systems. This includes integrating machine learning models, natural language processing, and other AI-driven functionalities.</li>
</ul>
<h3 dir="ltr">Required Skills</h3>
<p dir="ltr">To excel as an Automation Engineer, professionals need:&nbsp;</p>
<ul>
<li dir="ltr"><strong>Proficiency in Automation Tools:</strong> Familiarity with leading automation tools like UiPath and Automation Anywhere is crucial. It&rsquo;s these kinds of platforms that allow the development and roll out of automated processes.</li>
<li dir="ltr"><strong>Scripting Languages:</strong> Scripting languages like Python and JavaScript are vital for creating automation scripts.&nbsp;</li>
<li dir="ltr"><strong>Process Optimisation Skills:</strong> A strong understanding of process optimisation techniques is important. This involves analysing workflows, identifying bottlenecks, and implementing solutions to enhance efficiency and performance.<br><br></li>
</ul>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">Professionals who can take on these roles can make a huge difference in your organisation. So, taking a strategic approach to hiring is essential if you want to remain competitive in the ever-developing AI industry.&nbsp;</p>
<p dir="ltr">As you plan your recruitment for 2024 and beyond, remember to consider the key AI roles covered in this article. If you can take on top talent in these areas, you&rsquo;ll undoubtedly boost your technological capabilities, but also set yourself up for long-term growth, and success.&nbsp;</p>
<p dir="ltr">If you&rsquo;re ready to boost your business by growing your AI team, <a href="https://www.generativegroup.ai/contact-us/">get in touch with Generative today.</a> We&rsquo;ll help you find the AI professionals you need to keep you ahead in 2024 and beyond!</p>

Are you looking to create a more innovative and efficient business this year? AI’s definitely the way to go! And that’s why it’s more important than ever to get clued up on the hottest AI roles. 

What Are the Top AI Roles You Should Be Hiring For in 2024?

<p>The UK government has just made a <a href="https://www.gov.uk/government/news/ai-to-reduce-train-delays-speed-up-nhs-prescriptions-and-train-construction-workers-gets-32-million-boost" target="_blank" rel="noopener">significant investment</a> in the future of artificial intelligence, with &pound;32 million allocated to support nearly 100 AI projects. These initiatives are poised to revolutionise various sectors, from reducing train delays and speeding up NHS prescription deliveries to training the next generation of construction workers.</p>
<p>This funding, awarded to 98 projects across the UK, underscores the government's commitment to harnessing AI for public benefit. With over 200 businesses and research organisations involved, this investment is not just about innovation&mdash;it's about improving the everyday lives of people and ensuring the UK remains at the forefront of technological advancement.</p>
<p>&nbsp;</p>
<h2><strong>AI to Improve Public Services</strong></h2>
<p>AI's potential to transform public services is immense. Among the funded projects, a standout is the work of V-Lab Ltd, which received &pound;165,006 to develop AI-driven training simulations for the construction sector. These virtual simulations will help workers train in real-world scenarios, enhancing safety and ensuring the UK has a skilled workforce ready to meet the demands of future infrastructure projects.</p>
<p>The NHS is also set to benefit from this AI boost. Nottingham-based Anteam is leading a project to improve the efficiency of prescription deliveries. By using AI algorithms, they will optimise delivery routes, reduce carbon emissions, and improve patient experiences. This project exemplifies how AI can streamline processes, making vital services faster and more efficient.</p>
<p>&nbsp;</p>
<h2><strong>Enhancing National Infrastructure</strong></h2>
<p>The UK's railway network, a critical part of the nation's infrastructure, is also in line for a technological upgrade. Hack Partners is developing an autonomous system to monitor and manage railway infrastructure, aiming to significantly reduce maintenance time and improve safety. This AI-powered solution will help keep trains running smoothly, reducing delays and improving the overall reliability of the network.</p>
<p>&nbsp;</p>
<h2><strong>Supporting High-Growth Industries</strong></h2>
<p>Beyond public services, the funding is set to drive innovation in high-growth industries. Cambridge-based Monumo, for example, is working on AI technology to improve motor designs for electric vehicles. Their 3D Generative-AI Tool aims to enhance sustainability across sectors like commercial transportation, aviation, and power generation, contributing to the UK's efforts to lead in green technology.</p>
<p>In logistics, Robok Limited is using AI to optimise warehouse operations, while Kelp Technologies is collaborating with fashion retailers to streamline pricing in the second-hand clothing market. These projects not only promise efficiency gains but also support the UK's environmental goals by reducing waste and emissions.</p>
<p>&nbsp;</p>
<h2><strong>A Future Powered by AI</strong></h2>
<p>The &pound;32 million funding announced by the UK government is a clear signal of the country&rsquo;s commitment to AI-driven growth. These projects represent just the beginning of a broader effort to integrate AI into key sectors, driving productivity, enhancing public services, and ensuring the UK&rsquo;s global leadership in technology.</p>
<p>&nbsp;</p>
<h2><strong>Want to be part of this AI-driven transformation?</strong></h2>
<p>At Generative, we believe in the transformative power of AI. This government support aligns with our mission to leverage AI for positive change, and we're excited to see how these projects will shape the future. <a href="https://www.generativegroup.ai/contact-us/">Reach out to Generative</a> to explore how we can help you build an AI team with these cutting-edge skills that can transform the productivity of your organisation.&nbsp;</p>

Discover how the UK government's £32 million investment in AI is set to transform public services and boost productivity across the nation. From reducing train delays to speeding up NHS prescription deliveries, explore the innovative projects leading the way in AI-driven solutions. 

£32M Boost for AI to Cut Train Delays, Speed Up NHS, and Train Workers

<p dir="ltr">&nbsp;To truly harness the power of AI, you need the best minds in machine learning on your team. But in a competitive landscape, how do you ensure you're hiring the top talent?</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Introducing our exclusive whitepaper, "The Fight for Machine Learning Talent."</h2>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">Inside you'll learn how to:</p>
<ul>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Expand your approach to find the best ML candidates.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Learn how to adapt your criteria to capture a wider pool of talent.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Discover how to make your company irresistible to top engineers.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Master the art of interviewing to identify the best fits for your team.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Craft compelling offers that top talent can&rsquo;t refuse.</p>
</li>
<li dir="ltr" aria-level="1">
<p dir="ltr" role="presentation">Ensure your engineers are challenged, free to innovate, and motivated to stay.<strong><br></strong></p>
</li>
</ul>
<h2 dir="ltr">&nbsp;</h2>
<h2 dir="ltr">Why You Need This Report</h2>
<p dir="ltr">In the battle for machine learning talent, having the right strategies can make all the difference. Whether you&rsquo;re a multinational firm or a start-up, our guide provides actionable insights to help you secure and retain the best in the field.</p>
<p dir="ltr">Fill out the form below to download "The Fight for Machine Learning Talent" and start building your dream team today.</p>
<h2>&nbsp;</h2>

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<h4>The future of AI hinges not just on algorithms, but on the talented individuals behind them.</h4>

<h1>Find, Attract, and Retain the Brightest Minds in AI</h1>

<p>In today&rsquo;s competitive market, securing Machine Learning Engineers requires more than just traditional hiring methods. Whether you&rsquo;re a startup or a global enterprise, this guide provides actionable insights to give your business an edge in recruiting and retaining the best talent.&nbsp;Fill out the form below to download <strong>"</strong>The Fight for Machine Learning Talent."</p>

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The Fight For Machine Learning Talent

<h2><strong>With the recent <a href="https://www.theguardian.com/commentisfree/2024/apr/13/from-boom-to-burst-the-ai-bubble-is-only-heading-in-one-direction">boom in artificial intelligence</a> (AI), comes a boom in AI teams. And while the increasing popularity of AI means a wider choice of teams for professionals to work for, it means the competition for talent is higher than ever for those employing them.</strong></h2>
<p dir="ltr">The issue of employee turnover is a huge strategic challenge that AI employers are facing. As more and more companies are increasingly relying on AI talent to drive their innovation and ensure they stay heads and shoulders above the competition, retaining that top talent has become a top priority.</p>
<p dir="ltr">But if you&rsquo;re an employer in the world of AI, you&rsquo;ll know that there are very specific challenges when it comes to employee retention. There&rsquo;s the demand for specialised skills, plus the ever-changing nature of AI tech, not to mention the uber-competitive job market.&nbsp;</p>
<p dir="ltr">So, what&rsquo;s the secret to combatting retention issues? And how can you ensure you build (and keep) high-performing AI teams? The answer lies in implementing effective strategies that are as unique and dynamic as the AI sector you&rsquo;re part of.</p>
<p dir="ltr">In this blog post, we delve into key 5 strategies for minimising employee turnover within AI teams. If you&rsquo;re a tech exec/leader, a HR professional, or AI team manager, we&rsquo;ll provide you with actionable strategies for improving your retention rates and creating a culture of longevity and success within your AI teams.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr"><strong>1. Offer Competitive Compensation and Benefits</strong></h2>
<p dir="ltr">Because <a href="https://elblog.pl/2024/04/04/the-rising-demand-for-ai-talent-sparks-a-fierce-competition-among-tech-giants/">competition is so fierce</a> in AI, your offering must be equally as competitive. Providing attractive compensation packages and a broad range of benefits is a basic but fundamental strategy if you want to attract candidates and minimise employee turnover. And in AI, where expertise is in high demand, surely you want to fairly compensate people for the specialist skills they&rsquo;ve mastered?</p>
<p dir="ltr"><a href="https://www.pwc.co.uk/press-room/press-releases/research-commentary/artificial-intelligence--ai--exposed-sectors-see-a-fivefold-incr.html">Recent data</a> shows a steady increase in the AI sector&rsquo;s compensation levels. This is a direct reflection of the ever-increasing value that&rsquo;s placed on AI expertise. And with <a href="https://www.digit.fyi/83-of-uk-firms-increasing-wages-for-ai-skills-amid-challenges/#:~:text=Businesses%20are%20willing%20to%20pay%20a%20premium%20for%20AI%2Dskills&amp;text=In%20a%20rush%20to%20innovate,just%20seeking%20full%2Dtime%20hires">83%</a> of UK firms increasing wages for AI skills, it&rsquo;s clear that the industry's recognising the importance of rewarding talent appropriately.</p>
<p dir="ltr">In addition to competitive salaries, offering unique benefits can have a huge impact on employee retention within AI teams. Think about tailoring professional development opportunities or providing access to cutting-edge technology. Then there&rsquo;s one of the most highly sought after benefits right now: <a href="https://www.economist.com/business/2023/03/23/how-to-get-flexible-working-right?utm_medium=cpc.adword.pd&amp;utm_source=google&amp;ppccampaignID=18156330227&amp;ppcadID=&amp;utm_campaign=a.22brand_pmax&amp;utm_content=conversion.direct-response.anonymous&amp;gad_source=1&amp;gbraid=0AAAAADf4AbYjJkHx4MFnwv-3RHibgLy04&amp;gclid=CjwKCAjw1emzBhB8EiwAHwZZxTGB39G4aTL1-_1WC7WBmb3FOeRM5OK-mYBfwnM7beKdlkBnIHXNfhoCOBAQAvD_BwE&amp;gclsrc=aw.ds">flexible working</a>, that will help accommodate the dynamic nature of AI, plus will make you stand out as an employer of choice for AI professionals.</p>
<p dir="ltr">Ready to create a culture of retention and growth? You need to prioritise competitive compensation and innovative benefits.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr"><strong>2: Create a Positive Work Culture</strong></h2>
<p dir="ltr">Creating and nurturing a <a href="https://www.forbes.com/sites/pragyaagarwaleurope/2018/08/29/how-to-create-a-positive-work-place-culture/">positive work culture</a> is crucial if you want to retain employees. A supportive and inclusive work environment will not only boost employee morale and satisfaction but will also contribute to long-term engagement and loyalty.</p>
<p dir="ltr">Having a positive work culture can help people feel they belong which in turn results in collaboration and promotes open communication within AI teams. When employees feel valued, respected, and supported, they&rsquo;re far more likely to stay with your organisation and want to play an active role in its success. Because AI roles can be high-pressure, ensuring a positive working environment should be a constant consideration if you want to keep your employees healthy and satisfied.</p>
<p dir="ltr">Try implementing initiatives that prioritise diversity and inclusion. Think about things like <a href="https://uk.indeed.com/hire/c/info/what-is-unconscious-bias?gad_source=1&amp;gclid=CjwKCAjw1emzBhB8EiwAHwZZxeD-qwI-nelwoOkv6w7dPIxYTLf1taJXMQdPQnEgQu1Ac8vz5QBR1xoCVJoQAvD_BwE&amp;gbraid=0AAAAADfpQqvM7Fld7isoVip7tP9NBn0XM&amp;aceid=&amp;gclsrc=aw.ds">unconscious bias</a> training and mentorship programs, both of which can help create a more welcoming and equitable workplace for all team members. Additionally, organising team-building activities, hackathons, and knowledge-sharing sessions can strengthen bonds between colleagues.</p>
<p dir="ltr">A great work culture that values diversity, inclusivity, and teamwork, is a must-have for retaining AI talent. And the knock-on effect is a thriving and motivated workforce that drives innovation and success in the ever-evolving AI sector.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr"><strong>3: Invest in Professional Development</strong></h2>
<p dir="ltr">To stay ahead in AI and attract the very best talent, it&rsquo;s also important to invest in continuous learning and professional development. Technologies and methodologies in this space are advancing at an unprecedented pace, so to be an employer of choice you need to be providing opportunities for employees to upskill, reskill, and stay up to date with industry trends. Not only will this promote the growth of individual team members, it&rsquo;ll, ultimately, help with the success of your organisation too.&nbsp;</p>
<p dir="ltr">We all know how quickly AI is developing &ndash; the sector&rsquo;s characterised by constant innovation and technological evolution. And that&rsquo;s why continuous learning is important if you want your AI professionals to remain competitive and relevant. By investing in ongoing training and development, you&rsquo;ll demonstrate your commitment to supporting employees' growth and enhancing their skills in line with industry demands and standards.</p>
<p dir="ltr">Try offering a wide range of professional development initiatives &ndash; from structured training programs, and supporting attendance at conferences and workshops, to providing access to online courses and certifications. By doing so, you&rsquo;re empowering your employees to expand their AI knowledge and expertise.&nbsp;</p>
<p dir="ltr">Companies that <a href="https://businessadvice.co.uk/business-development/the-benefits-of-professional-development/">prioritise professional development</a> often reap the rewards of the most skilled and motivated workforces.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr"><strong>4: Provide Clear Career Pathways</strong></h2>
<p dir="ltr">Do you have clearly defined career pathways within your organisation? This is a crucial part of employee retention. By outlining achievable career trajectories and providing opportunities for growth and advancement, you&rsquo;re empowering employees to picture a future with you.</p>
<p dir="ltr">When you have transparent and distinct career paths, your employees know that their contributions are valued - and that there are opportunities for advancement within the business. In the competitive world of AI talent recruitment and retention, offering clear career progression paths will not only motivate employees to work hard and do well but will also instil a sense of loyalty and commitment to your company.</p>
<p dir="ltr">So how do you ensure you&rsquo;re demonstrating clear career progression routes for your teams? It&rsquo;s about outlining role expectations. But also communicating skill requirements for advancement and potential growth opportunities within the company. You can emphasise these pathways through regular performance reviews, one-on-one discussions, and by developing personalised career development plans.&nbsp;</p>
<p dir="ltr">Career development plans will provide employees with a roadmap for skill development, goal setting, and advancement, and are such an important tool in ensuring employees are both engaged and committed. And by implementing all these things, you can be sure that employees are aware of the steps needed to progress within their roles&hellip;and beyond.</p>
<p dir="ltr">Be sure to align individual aspirations with your organisational objectives. That way, you&rsquo;ll not only improve job satisfaction but also reduce turnover rates because you&rsquo;ve demonstrated a clear investment in employees' long-term success and fulfilment.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr"><strong>5: Enhance Employee Engagement and Recognition</strong></h2>
<p dir="ltr">There&rsquo;s a strong correlation between employee engagement, recognition, and retention. When your AI employees feel valued and recognised for their contributions, they&rsquo;re far more likely to stay committed to their roles and your company.&nbsp;</p>
<p dir="ltr">Did you know that employee engagement is the foundation for building a positive work culture, enhancing job satisfaction, and ultimately reducing turnover rates? By recognising and appreciating your employees' efforts and achievements, you&rsquo;ll not only boost morale but also reinforce their sense of belonging and purpose within the organisation. The result? Higher retention levels.</p>
<p dir="ltr">If you want to improve engagement and recognition within your AI team(s), look at applying strategies such as providing regular feedback on performance, establishing employee recognition programs, and creating a work environment that encourages a sense of purpose and collaboration. When you prioritise open communication, acknowledge accomplishments, and involve employees in decision-making processes, you&rsquo;re actively creating a culture of appreciation and engagement that drives loyalty and retention.</p>
<p dir="ltr">Examples of effective recognition practices in AI departments include peer-to-peer recognition programs, bonuses for outstanding performance, public acknowledgment of achievements (for example in team meetings) and personalised thank you notes or tokens of appreciation. The key is celebrating successes. When this becomes part of your everyday routine, you&rsquo;ll reinforce a culture of recognition, motivate employees, strengthen team dynamics, and ultimately experience higher job satisfaction and lower turnover rates.</p>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">In summary, minimising employee turnover within AI teams isn&rsquo;t straight forward, nor is it a quick fix. It takes time, dedication and planning. But once you&rsquo;ve implemented strategic initiatives like those covered in this article, you can proactively enhance retention rates and cultivate a high-performing AI team.</p>
<p dir="ltr">These strategies not only contribute to employee satisfaction and longevity but also position companies like yours as employers of choice. And that&rsquo;s so important in today&rsquo;s competitive AI talent market.&nbsp;</p>
<p dir="ltr">It&rsquo;s about committing to and investing in the growth, well-being, and recognition of your people. In return you&rsquo;ll create a culture of retention, innovation, and success within your AI teams, and beyond.</p>
<p dir="ltr">Are you ready to elevate your AI team and drive success through talent retention? Why not <a href="https://www.generativegroup.ai/contact-us/">reach out to Generative</a> today for expert guidance and support in building a resilient and high-performing AI workforce? We&rsquo;ll help you unlock the full potential of your AI team and achieve lasting success in the non-stop field of artificial intelligence.</p>

With the recent boom in artificial intelligence (AI), comes a boom in AI teams. And while the increasing popularity of AI means a wider choice of teams for professionals to work for, it means the competition for talent is higher than ever for those employing them.

5 Key Strategies to Minimise Employee Turnover in Your AI Team

<p dir="ltr">As we increasingly rely on tech at work, AI specialists are now key in our businesses for driving innovation and success. As companies look to work faster and better with the help of artificial intelligence, there&rsquo;s an increased demand for skilled professionals that can help them achieve their ambitious goals. And that means developing a hiring process that&rsquo;s more competitive than ever.</p>
<p dir="ltr">Hiring within AI can feel like a challenge. It calls for a deep understanding of the essential skills that set apart the very best AI specialists from the rest. So, to help we&rsquo;ve written this blog post in which we&rsquo;ll explore some of the core competencies that HR professionals, hiring managers, AI team leads, and recruitment experts should be prioritising when recruiting for AI talent. We&rsquo;ll equip you with the knowledge needed to make informed and strategic hiring decisions that&rsquo;ll help you to build the strongest AI teams for keeping you ahead of the game.&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Technical Skills</h2>
<h3 dir="ltr">1.&nbsp; &nbsp; &nbsp; &nbsp; Programming Languages Proficiency</h3>
<p dir="ltr">If you&rsquo;re looking to build a strong AI team, you&rsquo;ll want to find people who&rsquo;ve mastered programming languages. Python, R, and Java are known as some of the most common (and indispensable) languages for any successful artificial intelligence career.</p>
<p dir="ltr"><a href="https://towardsdatascience.com/data-science-learning-path-88fa39c469fb">Programming skills</a> are important and a basic requirement. In short, they&rsquo;ll enable AI specialists to design, implement, and optimise your AI algorithms and models. Python, known for being one of the most simple and versatile languages, is a firm favourite for tasks like data manipulation, statistical analysis, and machine learning model development. While R&rsquo;s good for statistical computing and visualisation, making it ideal for analysing and interpreting data in AI projects. And Java, known as one of the most robust and scalable languages, is typically used when companies want to build some of the highest-performing AI applications.</p>
<p dir="ltr">There&rsquo;s a whole host of programming languages now available, and by perfecting one or more of them, AI specialists will be able to help your company to overcome tech and operational challenges, plus drive innovation in your AI projects.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">2.&nbsp; &nbsp; &nbsp; &nbsp; An Understanding of Machine Learning Algorithms</h3>
<p dir="ltr">Next, let&rsquo;s look at why <a href="https://towardsdatascience.com/machine-learning-algorithms-in-laymans-terms-part-1-d0368d769a7b">machine learning algorithms</a> might be important when looking for AI professionals.</p>
<p dir="ltr">This crucial skill helps AI specialists grasp concepts like supervised learning, unsupervised learning, and reinforcement learning (i.e. to identify the right algorithms for the right tasks). Algorithms such as Random Forest for classification, Linear Regression for regression analysis, and Convolutional Neural Networks (CNNs) for image recognition, all play pivotal roles in AI projects. And, therefore, will be essential for your company&rsquo;s future AI success.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">3.&nbsp; &nbsp; &nbsp; &nbsp; Experience with AI Frameworks and Tools</h3>
<p dir="ltr">Being familiar with frameworks like <a href="https://www.tensorflow.org/">TensorFlow</a>, <a href="https://pytorch.org/">PyTorch</a>, and <a href="https://keras.io/">Keras</a> is an essential trait to look for in an AI specialist. Why? Well, it means they can streamline the development process of AI models and applications, which is essential if you want them to make applications quicker and ensure they perform well.</p>
<p dir="ltr">Frameworks like these provide pre-built modules and tools that make implementing complex networks and algorithms, much simpler. And, importantly, they provide AI specialists with additional time to focus on model architecture and optimisation. All important for an efficient AI team.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">4.&nbsp; &nbsp; &nbsp; &nbsp; Data Handling and Processing Skills</h3>
<p dir="ltr">Being good at data collection, cleaning, and <a href="https://towardsdatascience.com/data-preprocessing-concepts-fa946d11c825">preprocessing</a> should be a basic skill for any AI specialist. It helps them to ensure the quality and reliability of data used in AI projects.</p>
<p dir="ltr">If they have effective data handling, AI specialists can extract meaningful insights, identify patterns, and train accurate models - ultimately laying the foundation for successful AI solutions!</p>
<p dir="ltr">Tools like <a href="https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf">Pandas</a> and <a href="https://numpy.org/">NumPy</a> in Python help with data manipulation, cleaning, and transformation. And techniques such as feature scaling, outlier detection, and missing value imputation are all critical for making sure data integrity and enhancing the performance of models. So making sure anyone you&rsquo;re hiring has expertise in this area is key.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">5.&nbsp; &nbsp; &nbsp; &nbsp; Knowledge of Maths and Statistics</h3>
<p dir="ltr">A strong foundation in maths and stats is important for AI specialists as it helps individuals to understand and develop advanced algorithms and models.</p>
<p dir="ltr">Mathematics forms the basis of AI, and it provides the framework for understanding complex algorithms, optimising models, and accurately interpreting data and results. Statistics, on the other hand, equip AI specialists with a range of tools for analysing data trends that can help your business to make informed decisions based on facts - not just gut feeling/opinions.</p>
<p dir="ltr">When specialists have a strong background in maths and statistics, they&rsquo;ll feel empowered to tackle problems better, innovate more confidently, and achieve successful outcomes for your AI projects.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Soft Skills</h2>
<h3 dir="ltr">1.&nbsp; &nbsp; &nbsp; &nbsp; Problem-Solving&nbsp;</h3>
<p dir="ltr">Creative and analytical problem-solving skills should be near the top of your list of must-have qualities when looking to hire AI specialists.&nbsp;</p>
<p dir="ltr">Why? Well, in AI projects, specialists are often faced with a variety of challenges that require &lsquo;out-of-the-box&rsquo; thinking and innovative solutions. When they have the ability to creatively solve problems, they&rsquo;ll be able to&nbsp; come up with novel approaches to data preprocessing, model optimisation, and algorithm selection. And analytical skills will aid even further in identifying patterns, interpreting results, and troubleshooting issues that crop up during model development. Basically, AI professionals with problem-solving skills will be an asset to your organisation.&nbsp;&nbsp;</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">2.&nbsp; &nbsp; &nbsp; &nbsp; Communication Skills</h3>
<p dir="ltr">When AI specialists can articulate complex concepts to non-technical stakeholders, it&rsquo;s great for your business.</p>
<p dir="ltr">Clear communication can bridge the gap between technical and non-technical teams, ensuring that project goals, methodologies, and outcomes are shared concisely. Great communication also promotes transparency, boosts confidence and buy-in, and helps speed up decision-making processes. And this is so important in an area like AI which is new, brings about change and can come with challenges.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">3.&nbsp; &nbsp; &nbsp;&nbsp;&nbsp;&nbsp;Team Collaboration</h3>
<p dir="ltr">Tying in nicely with communication is collaboration. If you want your AI projects to thrive, effective teamwork and collaboration are essential. Teams can include a whole host of professionals - from data scientists and engineers to domain experts - that&rsquo;s why collaboration is so important.&nbsp;</p>
<p dir="ltr">Collaboration encourages knowledge-sharing, a range of diverse perspectives, and collective problem-solving. The result? Innovative solutions and successful project outcomes. And by bringing together the wide range of expertise from all of your unique team members, imagine the power the combined efforts of your AI specialists can have? It&rsquo;s key in achieving success in delivering the most exciting and innovative AI solutions.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">4.&nbsp; &nbsp; &nbsp; &nbsp; Adaptability and Continuous Learning</h3>
<p dir="ltr">Because AI never stands still, being adaptable and committing to continuous learning are both vital if you&rsquo;re an AI specialist.</p>
<p dir="ltr">The lightning speed of technological advancements means that AI specialists need to keep updated with the latest trends, tools, and techniques &ndash; it&rsquo;s essential for them to remain competitive in the industry. Only through continuous learning will professionals be able to acquire new skills, explore emerging technologies, and adapt to changing demands quickly.</p>
<p dir="ltr">A few of the best ways to stay informed include:</p>
<ul>
<li dir="ltr">attending conferences and workshops</li>
<li dir="ltr">completing online courses</li>
<li dir="ltr">engaging with research papers</li>
<li dir="ltr">experimenting with new algorithms</li>
<li dir="ltr">participating in hackathons or collaborative projects.&nbsp;</li>
</ul>
<p dir="ltr">AI specialists need a learning mindset. It&rsquo;s key to them enhancing their expertise and contributing meaningfully to the AI projects that will truly make a difference in your business.</p>
<p dir="ltr">&nbsp;</p>
<h3 dir="ltr">5.&nbsp; &nbsp; &nbsp; &nbsp; Attention to Detail</h3>
<p dir="ltr">Meticulousness plays an important role in developing accurate and reliable AI models that underpin successful project outcomes.</p>
<p dir="ltr">In AI projects, overlooking small details can lead to big problems in your organisation! Failing to pick up inaccuracies, biases, and problems with the performance of models can be catastrophic. But attention to detail avoids most of these issues.</p>
<p dir="ltr">&nbsp;</p>
<h2 dir="ltr">Domain-Specific Knowledge</h2>
<p dir="ltr">Domain-specific knowledge is vital in shaping the way AI applications are used in your business, dependent on the industry you&rsquo;re in and the end goals you have for your AI implementation.</p>
<p dir="ltr">In the healthcare sector, for instance, AI specialists with domain expertise can interpret medical data effectively, design predictive models for disease diagnosis, and optimise treatment plans based on clinical insights. Then, in finance, you&rsquo;ll want specialists who are well-versed in market trends and risk analysis - people who can develop robust algorithms for fraud detection, portfolio management, and algorithmic trading. Similarly, if you&rsquo;re in retail, you&rsquo;ll need someone who can help you to understand consumer behaviour, inventory management, and sales forecasting.</p>
<p dir="ltr">If you can combine technical proficiency with domain-specific knowledge, AI specialists can deliver tailored solutions that tackle&nbsp; industry-specific challenges, drive innovation, and provide new opportunities for you to grow and become more efficient.</p>
<p dir="ltr">&nbsp;</p>
<p dir="ltr">In this blog we&rsquo;ve highlighted the essential skills that HR professionals, hiring managers, AI team leaders, and recruitment experts should prioritise when looking to hire top-tier AI specialists. A strong AI specialist will possess a balanced skill set that includes both technical and soft skills. Ultimately, both are essential for succeeding in the dynamic world of AI.&nbsp;</p>
<p dir="ltr">It's about having AI specialists with the ability to not only develop advanced algorithms and models but also communicate them effectively. They&rsquo;ll also need to be able to collaborate with colleagues seamlessly and adapt to ever-evolving trends. That&rsquo;s what will make exceptional AI professionals stand out from the rest.</p>
<p dir="ltr">As organisations look to make the most of AI, it&rsquo;s important for hiring decisions to be based on a mix of a candidate&rsquo;s technical know-how and soft skills. It&rsquo;s about looking at the holistic skill set. And by doing so, HR professionals and hiring managers can ensure they recruit AI specialists with the capabilities to drive innovation, solve complex problems, and bring unlimited value to their organisations.</p>
<p dir="ltr">If you&rsquo;re not already doing so, it&rsquo;s time to put the development and acquisition of these key skills first. AI specialists are and invaluable piece of the puzzle in shaping the future of AI technology and driving the success of your business. If you&rsquo;d like to know more about how Generative can help you to attract and hire the very best AI specialists to your team, drop us a line and let&rsquo;s get the ball rolling!</p>

As we increasingly rely on tech at work, AI specialists are now key in our businesses for driving innovation and success. As companies look to work faster and better with the help of artificial intelligence, there’s an increased demand for skilled professionals that can help them achieve their ambitious goals. And that means developing a hiring process that’s more competitive than ever.

The Essential Skills to Look for When Hiring AI Specialists

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<div class="OutlineElement Ltr SCXW208165606 BCX0">
<p class="Paragraph SCXW208165606 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW208165606 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW208165606 BCX0">Specialists In</span></span><span class="EOP SCXW208165606 BCX0" data-ccp-props="{}">&nbsp;<br></span><span class="TextRun SCXW208165606 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW208165606 BCX0">Industry 4.0 Recruitment</span></span><span class="EOP SCXW208165606 BCX0" data-ccp-props="{}">&nbsp;</span></p>
</div>

<div class="OutlineElement Ltr SCXW148639536 BCX0">
<p class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">At Generative, we </span><span class="NormalTextRun SCXW148639536 BCX0">don&rsquo;t</span><span class="NormalTextRun SCXW148639536 BCX0"> just fill roles &ndash; we help businesses build the teams </span><span class="NormalTextRun SCXW148639536 BCX0">they need to thrive in the era of Industry 4.0. By focusing on Automation, Data, </span><span class="NormalTextRun SCXW148639536 BCX0">and AI/ML</span><span class="NormalTextRun SCXW148639536 BCX0">.</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></p>
</div>
<div class="OutlineElement Ltr SCXW148639536 BCX0">
<p class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">Far beyond just filling open roles</span><span class="NormalTextRun SCXW148639536 BCX0"> &ndash; </span><span class="NormalTextRun SCXW148639536 BCX0">W</span><span class="NormalTextRun SCXW148639536 BCX0">e </span><span class="NormalTextRun SCXW148639536 BCX0">leverage</span><span class="NormalTextRun SCXW148639536 BCX0"> or team</span><span class="NormalTextRun SCXW148639536 BCX0">&rsquo;</span><span class="NormalTextRun SCXW148639536 BCX0">s in</span><span class="NormalTextRun SCXW148639536 BCX0">-</span><span class="NormalTextRun SCXW148639536 BCX0">depth </span><span class="NormalTextRun SCXW148639536 BCX0">automation and AI </span><span class="NormalTextRun SCXW148639536 BCX0">expertise</span><span class="NormalTextRun SCXW148639536 BCX0"> to help </span><span class="NormalTextRun SCXW148639536 BCX0">streamline your hiring </span><span class="NormalTextRun SCXW148639536 BCX0">process and</span><span class="NormalTextRun SCXW148639536 BCX0"> achieve your goals.</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></p>
</div>
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<p class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">If </span><span class="NormalTextRun SCXW148639536 BCX0">you&rsquo;re</span><span class="NormalTextRun SCXW148639536 BCX0"> ready to build an agile &lsquo;Industry 4.0 ready&rsquo; team that</span><span class="NormalTextRun SCXW148639536 BCX0"> understand how</span><span class="NormalTextRun SCXW148639536 BCX0"> AI/ML, data, and automation </span><span class="NormalTextRun SCXW148639536 BCX0">can</span><span class="NormalTextRun SCXW148639536 BCX0"> propel your business forward, </span><span class="NormalTextRun SCXW148639536 BCX0">we&rsquo;ve</span><span class="NormalTextRun SCXW148639536 BCX0"> got the connections to </span><span class="NormalTextRun SCXW148639536 BCX0">secure the right talent</span><span class="NormalTextRun SCXW148639536 BCX0">.</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></p>
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<h5 class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">The Challenges We Solve </span><span class="NormalTextRun SCXW148639536 BCX0">For</span><span class="NormalTextRun SCXW148639536 BCX0"> You</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></h5>
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<p class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">We address the scarcity of specialised automation talent with our in-depth industry </span><span class="NormalTextRun SCXW148639536 BCX0">expertise</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></p>
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<li class="OutlineElement Ltr SCXW148639536 BCX0" role="listitem" data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1">
<p class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW148639536 BCX0">Slow recruitment processes disrupt timelines, but we deliver fast solutions to keep projects on track</span></span><span class="EOP SCXW148639536 BCX0" data-ccp-props="{}">&nbsp;</span></p>
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<p>Flexible Industry 4.0 Talent</p>

<p><strong>The Challenge</strong>&nbsp;</p>
<p>A major investment led to a significant expansion of their manufacturing capabilities, including new automation infrastructure. &nbsp;</p>
<p>The company needed urgent support to hire across Automation and MES roles to meet project deadlines. Existing suppliers struggled to deliver sufficient talent within budget&nbsp;</p>
<p><strong>Our Solution</strong>&nbsp;</p>
<p>We secured 15 engineers across both disciplines, strategically located in the US and EU, and provided end-to-end support with onboarding and logistics. &nbsp;</p>
<p>This allowed the company to meet project timelines and successfully complete their expansion.&nbsp;</p>

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<h2 class="Paragraph SCXW235710044 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW235710044 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW235710044 BCX0">Proven Results</span></span><span class="EOP SCXW235710044 BCX0" data-ccp-props="{}">&nbsp;</span></h2>
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<h5 class="Paragraph SCXW235710044 BCX0" lang="EN-GB" xml:lang="EN-GB"><span class="TextRun SCXW235710044 BCX0" lang="EN-GB" xml:lang="EN-GB" data-contrast="auto"><span class="NormalTextRun SCXW235710044 BCX0">Leading Biotechnology </span><span class="NormalTextRun SCXW235710044 BCX0">Manufacturing Company &ndash; East </span><span class="NormalTextRun SCXW235710044 BCX0">Coast, US</span></span><span class="EOP SCXW235710044 BCX0" data-ccp-props="{}">&nbsp;</span></h5>
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<p>Talent Solutions</p>

<p>Experience X Adaptability</p>

<p>Transparent</p>

<p>Global Talent Network</p>

<p>A Partnership for the Future</p>

<p>Pair that with our hyperfocus in AI &amp; Data and you'll gain a partner who can keep you at the forefront of the AI revolution.</p>

<p>Integrity&rsquo;s at the heart of Generative. We operate with complete transparency and are proud to maintain the highest standards. Client or candidate, you&rsquo;ll get a fair, respectful, and inclusive experience.</p>

<p>The best talent might not be on your doorstep, but tech and modern ways of working means there are no boundaries. Our extensive network spans the globe, and we&rsquo;re ready to connect you with top AI &amp; Data specialists from around the world.</p>

<p>Choosing us means more than just finding the next addition to your workplace; it's an investment in your organisation's future. We'll help you build a dynamic, innovative team that can help you get the most from AI &amp; Data.</p>

<p>Why Choose Us?</p>

<p>With quality at the heart of all we do, we're dedicated to ensuring our solutions are not just successful, but transformative &ndash; taking your career or company to the next level.</p>