Artificial intelligence was a major focus for leading thinkers in 2025, and Finalto’s specialists were no exception.
While observers remain divided on whether the current rate of investment in AI infrastructure promises a paradigm shift or a crash in the making, business leaders beginning to gain a clearer sense of how the technology might deliver practical value.
In the UK, a Deloitte survey of CFOs found that “59% of the UK’s largest businesses have become more optimistic over the past 12 months on the potential for AI to boost the performance of their own organisation”.
This marks a notable shift from the 39% recorded in a previous survey, conducted in Q3 2024. That’s interesting, given the rapid and widespread adoption of AI tools in the workplace in that time. Early adoption at the employee level appears to have strengthened, not weakened, executive optimism.
In the AI driving seat
The finding is notable, if, as McKinsey put it, “the biggest barrier to scaling is not employees—who are ready—but leaders, who are not steering fast enough.”
McKinsey’s research, published in early 2025, found that three times as many employees were using AI at work than their managers supposed. At the same time, the survey found, many executives cited employee readiness as an impediment to their company’s AI adoption strategy, a belief that stands in stark contrast to the reality of widespread employee adoption of AI tools.
The convergence of executive optimism and employee-driven adoption plausibly means that in 2026, companies will move toward more coordinated AI adoption, with leadership strategies starting to catch up to employee-level use.
The significance could exceed rates of adoption. Researchers at the London School of Economics found that most employees they surveyed has not received AI training, with the consequence, the authors suggest, of “leaving substantial efficiency gains unrealised”.
Integrated AI strategies, that guide adoption best practices and provide effective training, could be key to ensuring that adoption translates into tangible improvements in efficiency and productivity.
Strategic synergy
Of course, executive surveys help identify real-world risk as well as opportunities. A 2024 Deloitte report on AI and operational risk in banking found evidence of a new wave of technology-enabled threats, with 26% of leaders reporting their organisations had experienced deepfake incidents.
In this context, adequate training may not simply be a question of efficiency gains but also comprise part of an AI governance strategy.
In financial services, the need for strategies of accountability is becoming increasingly urgent and clear.
What should be clear by now is that neither top‑down strategy nor bottom‑up improvisation is enough on its own. Executives can set priorities and allocate budgets, but without visibility into how tools are actually used, those plans risk becoming detached from reality. Employees, meanwhile, have shown eagerness and ingenuity in adopting AI to improve daily workflows, but without strategic oversight, adoption remains fragmented and risks accumulate. The challenge for 2026 is to bring these together: strategy informed by practice, and practice supported by strategy.
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