The AI reality check UK financial services leaders won’t say out loud

There's a finding in new research on European technology leadership that isn't getting the attention it deserves.

UK financial services organisations are investing heavily in GenAI. At the same time, the technology leaders running those organisations say GenAI is receiving disproportionate attention relative to its actual strategic value. That's not a contradiction it’s a sector trying to reconcile board expectations with operational reality and not quite managing it yet.

This tension sits at the heart of The European Tech Leader's Breakthrough Moment, Fujitsu and Interbrand's research into 1,750 technology leaders across eight European markets. The UK financial services data tells a story that's more nuanced, and more useful, than most of what's being written about AI and the sector right now.

Technology confidence among European IT leaders is at an all-time high. In UK financial services, 82% of technology leaders say IT is seen as a strategic function by executive leadership. Boards are listening, CIOs are in the room and that’s a genuine shift from where the function sat a decade ago.

But the data carries a note of caution. Only 76% of UK financial services respondents are optimistic about the future role of their IT department, compared to 83% across Europe. That gap isn't pessimism. It's realism. Technology leaders in banking and insurance are operating under pressures their counterparts in other sectors don't face to the same degree: FCA and PRA accountability, DORA compliance, legacy estates underpinning services regulators expect to be continuously available, and a cyber threat landscape that is intensifying by the quarter.

UK banks alone are projected to spend over £2.5 billion annually1 on resilience and compliance through 2026. The stakes of getting technology decisions wrong aren't abstract here. They are financial, regulatory and reputational, sometimes all three at once.

Here's the finding worth sitting with.

The UK financial services Technology Investment Quadrant, which maps current investment urgency against ideal importance, places GenAI in the overinvested category. High current spend, lower strategic importance than that spend implies.

This isn't anti-AI sentiment. 70% of UK financial institutions have active AI projects and 40% are running GenAI proof-of-concept pilots2. The sector is experimenting, but its technology leaders are applying a level of scrutiny to those experiments that isn't always visible in the external narrative.

What this tells you is that a sector has learned, often the hard way, not to conflate investment with value. GenAI is absorbing significant budget and attention at a moment when the underlying foundations, resilience, infrastructure, data quality, still need serious work. The question isn't whether GenAI has a future in financial services, it clearly does, the question is whether it's getting resources in the right sequence.

78% of financial services respondents acknowledge that IT can't innovate or drive business growth while focused on managing legacy. That figure matches the European average, which tells you this isn't a UK-specific problem. But in financial services, where core banking platforms are heavily reliant on systems that slow cloud migration and increase operational fragility, the legacy burden lands differently.

With 90% of UK banks have migrated at least part of their core infrastructure to cloud3, cloud spend is projected to grow at 15% CAGR through 20264. The direction of travel is clear, but migration alone doesn't resolve the resilience problem. Moving fragile systems to the cloud doesn't make them less fragile it just changes where the fragility sits.

The regulatory expectation is unambiguous, by March 2025, UK banks and insurers were required to demonstrate they can withstand severe disruptions without breaching impact tolerances. Cybersecurity ranks as the single highest-priority investment in the sector, and it belongs there. The threat is real, the regulatory mandate is non-negotiable, and third-party failures have already triggered outages that boards won't forget.

There's a further risk worth naming directly Data Management and Intelligence sits in the low-priority quadrant of the current investment picture. That matters because AI's effectiveness depends entirely on data quality. Underinvesting in data infrastructure while overinvesting in AI applications is a sequencing problem that compounds over time, quietly. For technology leaders building an investment case, the data points in one direction: resilience isn't what you do before innovation. It's what makes innovation sustainable.