From experimentation to execution: the banks winning with AI

Artificial Intelligence (AI) in banking and wider financial sectors is rapidly becoming a story of the ‘haves’ and ‘have-nots.’ Those organisations who have adopted early, and more critically moved from experimentation to real-world implementation, are now pulling away from their competitors at pace. This split is not necessarily aligned with size, sector or location, but rather closely associated with approach to technology adoption and confidence in one’s own organisational governance.

Banks across the UK and US have a definite opportunity to capitalise on AI, supported by pro-innovation regulatory frameworks. Taking the critical first steps to move from good ideas to deploying valuable AI applications is time critical if you want to maximise the potential of this technology – those that move quickly and effectively stand to gain the most.

A favourable regulatory landscape

In 2024, the lack of clear regulatory direction in both the UK and US was a potential barrier to meaningful AI adoption in financial services. Without safety assurances, many organisations did not feel confident in the ability of generative AI (GenAI) to improve operations.

Now, the picture is a lot clearer. The focus is on growth, punctuated by the UK Government’s AI Opportunities Action Plan’ and the US Executive Order ‘Removing Barriers to American Leadership in Artificial Intelligence’. Both introduced in early 2025, they have helped to create a regulatory framework that isn’t overcrowded with red tape and keeps the focus on innovation and growth.

Contrastingly, the EU’s rule-based AI act has emerged as an obstacle for firms, contributing to a slower rate of AI adoption compared with the UK and US. Faced with a dense web of rules, that may be overly-technical, it’s no surprise that firms are struggling to extract real value from AI.

According to EY, just 9% of European banks consider themselves ahead of the competition in AI integration.

In the UK, however, banks have a green light from government to strike while the iron is hot and get ahead of their European counterparts on AI adoption. The UK’s approach aims to strike a practical balance between safeguarding against the risks of AI and driving innovation.

A growing role in banking

Banks are constantly striving to achieve maximum efficiency, and AI is set to play an even greater role in operations to this end.

Taking a step back, AI has already made its mark by reducing – and even removing – time consuming tasks in customer complaints, underwriting of credit and investigations of bad actors. However, we’re yet to see its true value in banking, which is likely to impact at a macroeconomic level.

Banks are now turning their attention to adopting AI in organisational areas where it has yet to scratch the surface. These include, although are not limited to, risk, finance, investments and wealth management. It’s here that banks will be seeking to use GenAI automation to lighten the load on employees responsible for the administrative burden of executive-level reporting, corporate facility applications, fund profiling, and Bulk Purchase Annuity data mapping.

Delivering long-term value

As banks oversee safe, sustained deployments of GenAI automation processes, confidence will build in their AI systems, models and users. We’re already seeing increasing use cases demonstrating better customer outcomes, which has the added value of increasing compliance efforts with the FCA’s Consumer Duty.

These new use cases aren’t so concerned with efficiency gains, but more so with improving revenue and client acquisition. Agentic AI, which can assess and act to achieve multi-dimensional goals independently (without human intervention), will be instrumental for leaders hoping to make these gains.

Large language models are also transforming the customer journey. By hyper-personalising the financial product offerings, we’ve already witnessed an uptick in revenue streams. Additionally, these models are helping banks to broaden their appeal by attracting and engaging new customers with personalised, human-like communications and interventions.

While many banks are already making progress, those that act decisively on AI adoption will see real results on long-term growth and positioning with competitors. The UK’s favourable landscape on AI governance provides the opportune moment to take the lead. However, success will also depend on strong and simple AI governance and adoption that ensures teams are equipped with the right skills.

Banks need to ensure their teams can provide the proper skills, oversight and confidence for AI adoption, whether this be through recruitment or internal training efforts. AI literate scientists, engineers, cyber security specialists and data-privacy experts will all be key. At the same time, organisations risk falling behind if they divert too much attention to maximising safety and not understanding the practicalities and value of GenAI for growth.

Gordon Baggott is Director of AI, 4most