It’s fair to say that AI is reshaping the Fintech landscape. Last year, UK-based startups in the sector raised $7.9 billion (£5.86 billion) in funding - an 80% rise on 2024¹.

This massive spike in investment and its inevitable impact was the basis for several thought-provoking discussions at our recent Innovation Day in London.

In addition to 1:1 meetings, the event brought founders, investors, thought leaders and policymakers together for passionate panel discussions on how to turn the extraordinary potential of AI into tangible value.

Although the afternoon panels all focused on a different challenge, there were a few key threads that emerged, including:

• The importance of defining purpose for AI startups
• Ways to tackle first-of-their-kind regulatory and compliance challenges, and
• Why businesses – large enterprises in particular – will be pressed to look beyond technology to unlock real value.

Here is a summary of each of these key discussion points.

One key theme repeated across several panels was the importance of purpose.

Increased investment means there is heightened competition between AI-powered fintechs, which may make differentiation more difficult, but also, more important.

With VCs and other investors assessing potential partnerships more closely than ever, with a clear eye on longevity and lifetime value, being able to answer key questions about purpose is essential.

In other words, it's not enough to be 'AI-powered'. Founders must be able to provide a clearly-defined vision for their offering and it’s specific use case, that they can defend to investors and buyers.

This means detailing in clear terms exactly what problems the technology is aiming to solve.

Panellists suggested that such propositions will be essential as the AI space evolves from assistance to autonomy. At present, many AI deployments still fall into the former category - offering support or greater efficiency for tasks. But in 2026, the most innovative firms are those that can make the leap to the next level, delivering truly autonomous AI agents that deliver measurable business outcomes.

This move from 'helping' to 'doing' could be make or break for AI Fintech providers. To succeed, they'll need to demonstrate tangible business value that answers questions about how AI might grow the bottom line, and not just boost efficiency.

Shifting regulation is a familiar challenge for fintechs, with AI amplifying the intensity and complexity of change.

Several panellists shared their views around risk management and the challenges of compliance more broadly, with specific concerns about issues like liability and data governance.

For example, who should be responsible for an agent or AI-driven system makes a mistake? The user, the vendor or the model itself? This is just one of many questions that must be answered as agentic AI in particular is integrated into large enterprises.

These evolving use cases and unanswered questions are expected to prompt regulators and risk management professionals to develop new guardrails to safeguard how data is used as new tech is deployed; which in turn could trigger further disruption. Flexibility in the face of change will be key – but not at the expense of a clear purpose.

Panellists also emphasised that regulators like the Financial Conduct Authority are learning at the same time as the industry, so at the moment, the attitude to risk remains collaborative and exploratory. As such, all businesses exploring AI should be prepared for shifting standards and plan for adaptability rather than one-off compliance.

One particularly insightful point raised was that while risk management is always a challenge, it doesn't have to be a blocker. Financial services is already a highly-regulated sector, so businesses and investors alike should have a strong understanding of risk.

As panellists suggested, it’s ambiguity - not regulation itself - that should be avoided.

Although the venue was packed with tech experts, a number of panellists pointed at that the biggest risks and challenges faced by businesses seeking to unlock value through AI aren't technical - they're organisational and cultural.

The core challenge in a rapidly changing space like fintech? Moving beyond multiple “proofs of concept” to viable, long-term business solutions that investors and customers alike can get on board with.

But what does that look like in practice?

For customers, getting stuck in an endless cycle of testing without embedding meaningful, enterprise-wide solutions is a bit like stepping into quicksand. This may well be a reason why startups that demonstrate deep expertise in one domain rather than biting off more than they can chew (and deliver on) seem to stand apart. Developing and mastering a focused solution is an accelerant that helps set new businesses apart while building confidence with investors and procurement teams.

It’s also worth remembering that no matter how revolutionary technology is, people ultimately buy from people – and that means storytelling matters. Founders are expected to be able to demonstrate that they have the specialist skills needed to support their partners, and often that means going beyond tech and jargon.

For established businesses hoping to unlock the value these solutions promise, there’s a need to match new tech with new ways of working and wider organisational change. Generating real value means transforming processes from end to end, which will require a full lifecycle rethink. As such it’s imperative that founders position their solutions as real value drivers rather than merely a means to cut cost.

Collaboration is central to these efforts in a world that’s rapidly being reinvented. Close collaboration between startups, enterprise partners and regulators is crucial in achieving this collective shift. As Emily Turner pointed out: