Tim Ryan walked into one of the toughest jobs in banking with eyes wide open. As Citigroup’s head of technology and business enablement, he oversees a near $12 billion annual tech budget. His mandate? Help CEO Jane Fraser move the 219,000-employee giant past years of regulatory headaches and creaky systems. And do it with artificial intelligence at the center.
Ryan, who joined from PwC in 2024, doesn’t chase flashy tools. He obsesses over adoption. In a recent interview, he laid out a philosophy that sets Citi apart from some Wall Street peers. “Don’t measure everything, because you’ll stifle it,” Ryan told Business Insider. “You have to measure the big things, but don’t try to measure every last-mile use case, because, frankly, you’ll uninspire people if they feel like they’re being watched too much.”
Short and direct. Yet it captures a tension playing out across finance. Banks pour money into generative AI. They tout productivity gains. Many install dashboards to track token usage or engineer velocity. Ryan wants none of that granular oversight at Citi. Pride matters as much as metrics, he argues. Overdo the watching and enthusiasm dies.
Fraser has made technology a cornerstone of her agenda since taking the top job. On the bank’s second-quarter 2026 earnings call, she and the CFO highlighted AI efficiencies. Nearly 90 percent of employees now use AI tools. A 4,000-person peer-to-peer training network scales knowledge fast. Agents for coding tasks are expanding. The message was clear. Citi isn’t waiting for disruption. It’s forcing change from within.
But Ryan’s approach stands out. He believes the winners won’t be the banks with the best large language models. Success hinges on something harder. Bringing tens of thousands of people along. “I don’t think you’ll hear anybody stand up and say I won because I chose this LLM or this LLM,” he said in the same Business Insider interview. “Where they will win or lose is how they bring tens and tens of thousands of people along.”
That focus shows in concrete steps. Last fall Citi rolled out mandatory prompt training to 175,000 employees across 80 locations. The internal memo, co-signed by Ryan and chief operating officer Anand Selva, drove the point home. “Just as the right question in a client pitch can reveal clarity and create advantage, a well-crafted prompt can accelerate your work, surface insights and amplify your impact,” it read, according to Fortune.
Employees had already entered more than 6.5 million prompts into Citi’s tools that year. The bank reported work once measured in hours now completed in minutes. Peter Fox, Citi’s head of learning, explained the module’s design. It uses an adaptive platform. Experts finish in under 10 minutes. Beginners take about 30. The goal remains straightforward. Move from basic prompting to great prompting that delivers real results.
Ryan reinforces the message on LinkedIn. In posts reflecting on investor day, he noted technology spending increasingly targets durable returns and client experience improvements. The bank has embedded AI into more than 50 of its largest workflows spanning 84 countries. Over 70 percent adoption in key areas. One million automated code reviews freed up 100,000 engineering hours per week. Those hours, Ryan stresses, must convert into client value. Not just cost savings.
Yet the transformation carries real costs. Citi committed in 2024 to cut as many as 20,000 positions over three years. Headcount now sits at 219,000. Ryan acknowledges the fear among engineers. AI raises obvious questions about job security. He avoids tying layoffs directly to the technology. Instead he emphasizes smart hiring. Trim contractors. Grow into new roles. Communicate openly. “What I can control is making sure we’re being smart about hiring, so we can make sure we grow into growth and minimize the number of pressure layoffs,” he explained to Business Insider. “We’ve been incredibly open about that with our people, and while it doesn’t take the fear away, it reduces it and tries to help people focus on what they can control.”
Contrast that restraint with industry moves. JPMorgan built AI dashboards for its engineers. Goldman Sachs tracks team velocity. Some firms cap weekly token spend as costs climb. Ryan tracks overall spend with clear return-on-investment thresholds. He pushes teams toward lower-cost models when they suffice. “You don’t need a Ferrari to do some of the stuff,” he said. The bank can’t afford to fall behind on cost discipline. But it refuses to let measurement become micromanagement.
Fraser’s broader reset sets the tone. In a memo obtained by Business Insider, she declared the bar raised for 2026. Bad habits must go. Scale, ownership, accountability and innovation take priority. “Let’s get it done,” she wrote. Ryan, along with banking head Vis Raghavan and wealth leader Steve Sieg, forms part of her handpicked team to execute that vision. His steady consulting background brings credibility to the tech overhaul.
Challenges remain. Data quality issues drew Federal Reserve and OCC scrutiny in recent years. Fraser has tied modernization efforts directly to fixing those problems. Hundreds of AI use cases now run across the bank. But turning pilot projects into enterprise change demands consistent adoption. Ryan’s refusal to track every interaction aims to preserve creativity. Whether that bet pays off will show in client outcomes and financial returns.
And the competitive pressure keeps building. JPMorgan posted record profits this quarter. Peers pour billions into AI infrastructure. Citi’s stock and performance face constant comparison. Ryan’s measured style, focused on human factors over pure technology, offers a different path. One that treats employees as partners in the shift rather than data points.
So far the early signals look positive. High usage rates. Growing agent deployments. Visible productivity anecdotes. But banking technology transformations have a long history of overpromising and underdelivering. Ryan knows the score. He didn’t want an easy job. Citi’s complex legacy systems and global footprint guarantee that. The real test lies ahead. Can the bank sustain momentum without over-measuring? Will the people-focused strategy deliver the durable growth Fraser demands?
Ryan’s answer rests on balance. Measure what matters. Inspire the rest. In an industry racing toward automation, that stance feels both radical and pragmatic. Banks will spend heavily on AI this year and next. The ones that win may be those that remember technology ultimately serves people. Not the other way around.
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