AI is no longer optional in banks. The roadmap, and showing how it pays off, is the hardest part.
Alexandra Mousavizadeh, co-founder and co-CEO of Evident, which tracks the use of AI in the financial sector, said some AI capabilities are currently “table stakes” for banks – think back-office functions like legal document review and routine onboarding tasks. But beyond that, Mousavizadeh’s banks must redouble their efforts to strengthen their “competitive advantage”.
“If you have a lot of your business in a certain area, banks there will double down on their investment in AI,” she said. For firms with a significant wealth management business, this could mean helping advisors better analyze client data; for more retail-focused banks, this could mean prioritizing chatbots and customer engagement.
Banks are investing billions in AI, and the technology is expected to redefine 44% of the work done there by 2030, according to consulting firm ThoughtLinks. JPMorgan, which ranks first in Evident’s AI maturity rankings, has invested at least $2 billion in technology and is deploying tools across its workforce of more than 300,000.
However, some investors and analysts are starting to question the returns. During their latest earnings calls, executives at several high-growth banks fielded questions about when AI-driven productivity and revenue gains would start showing up on balance sheets. Banks are under pressure to show that AI is helping them gain an edge.
Mousavizadeh said banks that have taken a “centralized” approach to technology decisions are often able to act more quickly and integrate AI more seamlessly.
His comments on integrating AI into key areas of business echo those of Dan Priest, director of AI at consultancy PwC, who previously told Business Insider that companies that took a “crowdsourcing” approach to AI adoption had a “pretty disappointing” return on investment.
Priest said moving to a “top-down” approach has proven more effective, allowing customers to focus on fewer tools and gain greater mastery over a smaller set of tasks.
AI agents are a priority as banks work to prove their AI spending is worth it, but Mousavizadeh said adoption is still in its early stages, particularly in external roles, like bankers and traders. In these cases, agents will likely be combined with humans for the foreseeable future as banks, some of the most regulated businesses, determine what guardrails to install.
Over the past six months, Goldman Sachs has been working with Anthropic on co-autonomous AI agents that can automate business tasks, including trade and transaction accounting and customer onboarding. Bank’s tech chief predicts agents will launch ‘soon’ and says it’s too early to think they’ll lead to job losses, CNBC reported.
How banks measure AI gains
Over the past year, banks have changed how they measure AI success, Mousavizadeh said, moving from tracking specific use cases to scaling capabilities. They are thinking about how to apply capabilities from one line of business to others and build an internal “architecture” that allows AI to reconfigure workflows enterprise-wide.
Achieving this scale requires a combination of top-down and bottom-up approaches. Banks need to put technology in the hands of every employee, Mousavizadeh said, and mandatory training often yields better results.
But mandates alone are probably not enough.
“AI is a fun thing. You need a culture where there is a lot of creativity,” Mousavizadeh added.
When it comes to the future of embedded AI, Mousavizadeh said banks have a new “north star”: What will a fully AI-integrated bank look like in a few years?
“You have to be able to come back from that,” she said.
More than applying AI to pre-existing products, this means creating new systems that reflect the bank of the future – and doing it faster than your competitors.
