Scott Wilson, Founder of Covecta, isn’t here to hype AI. He’s here to make it work.

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.

In this conversation, Scott shares what it really takes to scale AI at the enterprise level, why human oversight is evolving – and why now’s the time to join the team shaping the agentic layer of the future.

What specific problem is your startup solving and why does it matter right now more than ever?

We’re solving a widespread productivity and growth challenge in financial services.

In many Western economies, productivity has stagnated – largely because organisations haven’t modernised their tech infrastructure fast enough. Instead, they’ve leaned on growing headcount, which only adds cost without addressing the underlying issues.

Our AI agents are purpose-built for financial services. They help optimise operating models and redirect investment toward technology that enables scalable, sustainable growth.

And why now? Over the past three years, we’ve seen rapid AI adoption. What started with ChatGPT’s consumer-level impact has evolved into mature enterprise capabilities – 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?

What's the origin story behind Covecta?

Covecta’s founders have backgrounds in financial services and enterprise technology. We’ve seen the challenges in this space firsthand and have worked together long enough to build the trust and understanding that’s essential for starting a business.

We believe the opportunity here is huge. And if we get it right, we’ll unlock value not just for the industry, but for Covecta and our team as well.

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?

There’s a common fear that AI will replace humans, but history tells us otherwise.

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’s here to augment human capabilities, and not always replace them.

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’ll see is a rebalancing: people moving into roles where they can be most effective, just as we have in every major technological shift.

The key to getting comfortable with AI is education – 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.

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’ll measure success. Without that, adopting AI risks being directionless and ineffective.

For you and the team at Covecta, what does ‘AI safety’ look like in practice?

Every AI vendor has a responsibility to ensure safe and secure deployment… from addressing social bias to protecting confidential data. That’s non-negotiable.

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’s more stringent approach (including the EU AI Act) comes with important safeguards, but also risks slowing growth and competitiveness.

Ultimately, it’s about striking the right balance. Strong governance and global responsibility are essential, but so is ensuring that regulation doesn’t stifle progress.

What have you found to be the biggest challenge when bringing your product to market at scale?

Our biggest challenge – and it’s an ongoing one – is scaling the product while maintaining impact and quality.

As we work with more customers and prospects, the volume and complexity of product requirements increase. A key focus will be to ensure we’re prioritising the features that will deliver the greatest value to users.

At the same time, we’re building an engineering engine that can consistently ship high-quality AI capabilities at scale. That’s not a one-off effort. It requires continuous delivery, reliability, and a sharp focus on value. If we’re not delivering meaningful impact, organisations will look elsewhere.

What kind of team are you building at Covecta, and what qualities or roles are you looking for as you grow?

We’re a lean team by design. In the era of AI, you don’t need bloated teams… you need people with the right expertise and mindset.

We’re looking for individuals with deep domain knowledge in either AI or financial services. If you have both, we definitely want to talk.

We value people who can handle complexity and ambiguity, and who are motivated to help reshape the operating model of one of the world’s largest industries. There’s a new agentic layer emerging in the tech stack – and joining Covecta means being at the forefront of building that.

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.

I’m excited to share that we’re now hiring across the business. Our immediate focus is growing the product and engineering team – from DevOps and full-stack developers to AI/ML engineers. We’re also expanding commercially. But above all, we’re focused on shipping high-quality products at scale, and we want people who are excited to help make that happen.

Tell us more about the AI engineering role in particular!

As we grow, our core focus remains on building autonomous, specialised AI agents. Getting that right is critical to Covecta’s success.

We're developing a highly verticalised solution for financial services, which means understanding customer workflows deeply and delivering outputs with real relevance and context.

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 – you’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.

This is a fantastic chance to shape the agentic layer of a new tech stack in one of the world’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.

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.

In terms of AI trends, what’s genuinely exciting to you right now?

What’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.

One major shift we’re seeing is a move from human-in-the-loop systems to fully agentic solutions. In this model, humans aren’t completing tasks – they’re overseeing a team of AI agents, stepping into a managerial or supervisory role. That’s a significant change in how we think about work.

What stands out is how quickly financial services is moving in this direction. It’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’s largest industries, the ripple effects of this transformation will be felt widely – and that’s where it gets really interesting.