Banks have been trying for years to implement artificial intelligence (AI) programs to improve their client experiences and fend off increasing competition from new entrants outside the traditional financial services industry. Our report, "The AI Revolution In Banking," shows that these efforts have delivered only modest success so far, in large part because the programs haven’t cut broadly enough across the enterprise.
Some of the biggest potential benefits of AI for banks are in revenue improvement, yet most firms aren’t capturing them. But a small handful are making real progress. We call them AI trailblazers, and they are drawing a map for others to follow as they try to protect market share from potentially disruptive fintech and big tech rivals.
AI is already delivering measurable results in banking
What sets these trailblazers apart is not just ambition, but results. At some banks, AI is already driving around 10% of personal and auto loan sales through smarter targeting, while better pricing models have lifted net income in lending portfolios by up to 5%. Elsewhere, AI tools are catching far more fraudulent transactions than before and handling huge volumes of customer queries without human support.
Exhibit 1: Four pillars of AI transformation in banking
Banks succeed with AI by embedding it, upgrading data, and building AI teams
We have identified four steps the most successful banks in AI deployment are following. First, they aim to embed AI across the entire organization, not just in customer-facing tools but throughout front, middle, and back-office functions. Second, they adopt the mindset of technology companies, using agile ways of working and closer collaboration across teams. Third, they strengthen their data foundations by improving governance, quality, and infrastructure, often supported by cloud adoption. Finally, they build internal AI factories, bringing together specialized talent to scale AI across the business rather than relying on isolated initiatives.
In our report, we outline what sets these trailblazers apart and offer a clear roadmap for banks looking to accelerate or reset their AI journeys. It begins with a focused set of high-impact use cases that can deliver value quickly, then expands across the business while upgrading data, technology, and ways of working in parallel. It also calls for building multidisciplinary teams, investing in talent, and embedding AI into day-to-day operations rather than treating it as a standalone initiative.
The window to act is narrowing. According to the report, 56% of customers surveyed said they would consider switching to a banking proposition from companies like Google or Apple, while new competitors continue to gain ground and technology players move closer to core banking territory. Banks that act now still have a chance to stay relevant. Those that hesitate risk being pushed out of the conversation altogether.
Originally published in 2022.
