Role of Gen AI in Accelerating Digital Transformation in Financial Services

If the financial sector were The Matrix, generative AI (GenAI) wouldn’t be Neo—it would be Morpheus. Not the chosen one, but the brilliant strategist who expands possibilities while also ensuring the system doesn’t collapse under its own weight. Yet, many institutions are treating AI like an all-powerful saviour, rushing to integrate it without a clear blueprint. 

Right now, most institutions are deploying AI for obvious, labour-intensive tasks—important but limiting. It’s the classic trap of new technology: when engines were first invented, no one saw them as capable of powering spaceflight; they were just treated as a means to replace costly manual labour in the Mines and Cotton Mills of the British Midlands. If banks only use AI to cut costs, they risk missing its full potential—reshaping financial services at a strategic level.

Enterprise AI First

To unlock this, AI must be more than a patchwork of business unit projects—it must be an enterprise-wide function, much like HR or finance. That requires a dedicated AI team, led by a senior executive reporting to the COO, ensuring AI is embedded across operations, not confined to fragmented initiatives. This team should combine AI specialists with experienced business leaders— people from the spectrum of Banking products – from Money Markets to Mortgages, Prime Brokerage to POS terminals - ensure AI solutions are built with real industry insight.

Most importantly, AI must also be positioned as a co-pilot, augmenting human decision-making rather than replacing it. Without a structured AI function, banks risk fragmented adoption, regulatory breaches, and missed opportunities. A well-integrated AI function ensures AI is subject to strict oversight, preventing costly errors and driving real transformation.

By embedding AI at the core of the organisation, banks can move beyond short-term automation to optimising risk, uncovering new business opportunities, and delivering smarter, more personalised customer experiences.

AI for Hyper Personalisation

One area where AI is already transforming financial services is customer experience. Applying for a mortgage or car loan often means drowning in paperwork, frustrating customers before they’ve even begun. Ironically, once the product is in place, interactions drop to near zero. AI is addressing this imbalance by simplifying onboarding, reducing documentation, and ensuring real-time, intuitive communication.

Banks have long struggled to engage customers at the right moment. Historically, retail banking relied on mass emails or rigid customer life cycle models to push products, often missing the mark. Generative AI is changing that by analysing real-time behaviour and making tailored recommendations at the precise moment a customer needs them.

FinTechs have led the way by solving high-impact problems—like making trade finance about frictionless communication rather than rates. Banks are now doing the same, using AI to enhance customer moments. AI-driven assistants help Private Bankers simulate portfolios instantly and generate tailored proposals, while Contact centres use AI to transcribe, analyse, and provide real-time solutions.

Still, AI-driven personalisation is far from fully realised. Compliance and privacy concerns limit data use, and managing regulatory risks remains a challenge. The next step is balancing AI’s intelligence with trust—anticipating customer needs without overstepping boundaries.

The UK’s Financial Conduct Authority (FCA) has updated digital innovation guidelines, emphasising security, transparency, and compliance. Financial institutions must align with these while leveraging AI’s benefits through ethics committees, audits, and transparent decision-making.

The financial sector is in an exploratory phase with GenAI, like blockchain a decade ago—high enthusiasm but little strategic direction. Without a structured AI framework, institutions risk solving yesterday’s problems instead of building for the future. AI’s role in financial services is to enhance decision-making, optimise operations, and unlock efficiencies—but always with oversight. The winners will be those who treat AI as a disciplined, enterprise-wide transformation strategy.