Capgemini: Why AI is Redefining the Future of Banking

Gareth Wilson, Executive Vice President, Global Banking Industry Leader at Capgemini, believes "the AI revolution is here". 

Capgemini works with financial institutions around the world, harnessing technology to help them meet customers’ digital expectations, manage risk and drive strategic growth.

For more than 30 years, Gareth has been fortunate to lead large-scale and complex engagements for some of the industry’s biggest names.

You can hear more from Gareth in The Future of Finance panel discussion at AI LIVE: The London Summit on 21 October, taking place at Olympia London.

The session will explore AI in financial services, including risk modelling, fraud detection, algorithmic trading and customer personalisation.

To find out more about the event, click here.

How is AI redefining the future of banking?

The AI revolution is here. Adoption has accelerated across all age groups and is now an integral part of our daily lives – and financial institutions are embracing this shift. 

We are seeing AI deliver measurable business value across three critical fronts: driving efficiency gains through faster decision-making, greater accuracy and the automation of increasingly complex workflows; enabling entirely new operating models with autonomous, task-specific agents that were previously impossible; and accelerating innovation and growth by streamlining product development and expanding access to underserved markets. This combination is where I see the greatest potential in banking. 

To give you a sense of the scale of AI’s impact in banking today, Wells Fargo expanded its customer reach by launching Spanish-language support through its AI agent, Fargo and handled over 245 million interactions in 2024, up from 21 million in 2023.

Fargo’s growth is a preview of how AI agents can now deliver always-on support across different platforms while reducing wait times and boosting client satisfaction.

What's the biggest AI opportunity for financial services today?

Financial institutions have been early adopters of this generational technology, but today’s advancements are pushing the boundaries of what is possible. As these models have evolved, they're now able to reason, which is a big boost from a productivity standpoint.

Banks and insurers plan to make some of their key frontline processes AI-agent led by 2028. Customer onboarding and KYC display real promise. Across financial crime, expect faster investigations and materially lower compliance costs – in some cases, seven-figure annual savings – as AI agents make autonomous, real-time decisions to stay compliant.

The challenge is moving from pilots to enterprise-wide adoption. Our research shows only 10% of financial institutions have deployed AI agents at scale. This is because agentic AI is a complex, multi-dependency programme. One where governance, data, models, controls and company cultures are evolving together.

Although, when done right, the potential is endless to reshape how services are delivered and how customers engage with the brand.

How can banks innovate responsibly with AI?

For a heavily regulated industry like banking, there is a sense of cautious optimism around AI. While that is understandable, many of the same executives approaching AI with caution are also investing heavily in it to gain a competitive advantage.

We’re seeing a wide range of pathways as banks chart toward AI-centric financial services. Some rethink foundational workflows. Others find levers to optimise productivity, then using the savings realised to fund transformation.

Whatever the approach, responsible innovation must start with trust. That means embedding explainability, accountability, safety and governance into AI from the outset, ensuring your employees and customers understand how decisions are made and have confidence in the outcomes. 

Equally important is the human element. I cannot overstate the importance of having a workforce that can effectively work alongside AI. Banks that rely on external recruitment create a dependency model that is unsustainable. We need to invest in reskilling at scale, enabling employees to develop new capabilities and creating a culture that fosters human-AI chemistry.

How is AI reshaping the customer experience?

AI is fundamentally reshaping how banks engage with their customers. The era of restating your inquiry multiple times to employees at the same bank is over. Customer experience is being reshaped through real-time, contextual decision-making and hyper-personalised services. And even a small amount of friction is enough to send customers elsewhere.

Bank of America’s virtual assistant Erica exemplifies how AI enhances customer experience in banking today. Erica provides personalised financial insights and recommendations, helping customers manage their finances more effectively. The assistant analyses spending patterns and offers tailored advice based on individual financial behaviours. 

We are also seeing customers increasingly use AI agents to make decisions and complete tasks on their behalf. In this situation, companies will need to optimise for AI agents and human users.

As these new engagement layers emerge, the quality and accuracy of outcomes, such as whether an AI agent can identify the most suitable loan with the best rate for a customer, may become more important than having the best-looking interface.

What should bank leaders prioritise to stay ahead in the AI era?

There is a tendency to boil the ocean when it comes to AI. Our guidance to clients is to start with a clear roadmap: what are you trying to achieve, and how will AI help advance your business objectives? The most successful banks, big or small, are not chasing every new technology.

They are grounding their focus on pre-defined outcomes and targets, discontinuing pilots that don’t demonstrate measurable impact, and periodically reviewing progress to prove impact before scaling further. When decisions are grounded in the bank's purpose and supported by a clear vision for operations, risk, and culture, it becomes much easier to separate signal from noise.

The companies succeeding, however, share one thing in common: they engineer for scale from day one. They’re not just building smarter agents, they’re building business‑ready agents. At Capgemini, this is why we designed OrchestrateAI, a platform to help banks instantly deploy a suite of pre-built agents that work across all major AI models and cloud environments.

Because the challenge for banks isn’t identifying use cases; it is moving them into production with the confidence to tackle really complex business challenges.