Gen AI Adoption In Banking To Rise, But Business Models Not Keeping Pace With Innovation: IBM Study

The banking sector is seeing a significant change in the way generative artificial intelligence is being used, with organisations moving from extensive experimentation to a business strategy that places an emphasis on focused uses of the technology. However, an IBM survey has raised a bit of concern about how artificial intelligence adoption is happening in the banking sector.

As banks and financial institutions prepare for a critical year of investing in talent, technology, and transformation, they are expected to focus their efforts on gen AI projects that will improve customer experience, increase operational effectiveness, lower risks, and update IT infrastructure, a new study from IBM Institute for Business Value shows.

According to the study—which analysed C-suite leader sentiment, customer behaviour, and economic data from eight markets, including India—gen AI adoption in banks is set to soar. However, in a surprise, just 8% of banks were developing gen AI systematically in 2024, and only 78% had a tactical approach. As banks move from pilots to execution, more are redefining their strategic approach to service expansion, including agentic AI. 

Approximately 60% of banking CEOs surveyed agreed that in order to take advantage of automation and boost competitiveness, companies must be willing to take on a certain amount of risk. Additionally, contrasting financial performance is replacing steady banking convergence. According to the report, rethinking the company strategy and procedures as well as, crucially, execution would set the winners apart from the others.

More than 16% of banking customers feel at ease using a purely digital, branchless bank as their main financial relationship. Competition, however, is moving away from mass market digital offers towards higher-value services, such as advisory services and integrated finance for wealthy investors and small and medium-sized businesses.

Banking business models aren’t keeping up with client demand and AI-led innovation. To overcome this, banks must revise business strategies by changing the way clients are catered to; expand capability to serve clients with embedded finance, allowing them to do banking anywhere, anytime; enhance advisory propositions with AI to capture new service fees; and reconsider payment initiatives as the backbone for new data to fortify AI-powered risk management across ecosystems, the study suggested.