JPMorgan Chase CEO Dimon: We can't predict AI winners and losers yet

JPMorgan Chase CEO Jamie Dimon and the bank's C-suite issued annual shareholder letter that collectively shed light on the company's AI strategy, but perhaps the biggest takeaway is that "at this time, we cannot predict the ultimate winners and losers in AI-related industries."

Dimon's big message is that JPMorgan Chase will deploy AI as it would any other technology, but the landscape is changing fast. The subtext is that IT buyers need to keep their options open. JPMorgan Chase's annual technology budget is pushing the $20 billion mark.

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Some choice quotes from Dimon's letter:

• "We will deploy AI, as we deploy all technology to do a better job for our customers (and employees)."
• "AI will affect virtually every function, application and process in the company. And in the long run, it will have a huge positive impact on productivity."
• "We do not yet know exactly how AI will unfold. The landscape will change rapidly, with shifting assumptions about power consumption, costs, chip technologies and the speed at which data centers are deployed. There will be a wide variety of AI models — open and closed, large and small — and no single tool will dominate. Overall, the investment in AI is not a speculative bubble; rather, it will deliver significant benefits. However, at this time, we cannot predict the ultimate winners and losers in AI-related industries."
• "AI will definitely eliminate some jobs, while it enhances others. Our firm will have definitive plans on how we can support and redeploy our affected workforce."

He added that three are significant cybersecurity issues with AI and labor may not have time to adjust to the pace of AI. Dimon also said that you'll need to widen the lens on the impact of AI. He said:

"Huge technological shifts like AI always have second and third-order effects as well that can deeply impact society. Some of these are, for example, cars bringing about the development of suburbs and shopping malls; agriculture enabling cities; and the original internet (invented back in 1969) leading to mobile phones, apps and social media. We should be monitoring for this kind of transformation, too."

Jennifer Piepszak, Chief Operating Officer at the JPMorgan Chase, said the company's technology budget for 2026 is $19.8 billion. The focus is AI, platforms that are agile and the data core. Productivity gains will be reinvested. "Data powers it all — and data remains a competitive advantage. We’ve run one of the world’s most sophisticated financial data operations for decades, and that scale is a strategic asset. Data is powerful not simply because of its volume; when it is AI‑ready and consumable at the point of decision, it allows the right insights to drive better outcomes," she said.

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Small teams required for AI

Piepszak said AI requires changes in how JPMorgan Chase works. For starters, smaller teams need to be enabled to make decisions quickly and execute. To execute, these teams need platforms that are modular and scale efficiently. "

We’re already seeing productivity gains that will free up capacity, which we will reinvest in growth. We will continue to upskill, reskill and redeploy talent as technology evolves and productivity increases. While it will likely be the outcome in certain jobs, the goal is not fewer headcount; the goal is compounding performance with a growth first mindset," said Piepszak.

Dimon's letter emphasized that the company is organizing around small teams. "The teams needed to tackle these challenges should be small and authorized with the decision-making ability to move," said Dimon. "You need a team 100% dedicated to the mission. Success requires speed, agility and relentless execution.

These smaller teams need platforms too and some of them can't be vibe coded. He said:

"While there is an unbelievable need for speed, these teams can’t all build their own systems. They need to rely on a common language, common tools and interoperability. Therefore, certain platforms (e.g., for data, AI, coding, financial and CRM systems) need to be companywide and easily deployed, which may mean they are necessarily large. Before they are deployed, it may require consensus that they are the best platform to use. This makes them reusable and highly efficient. The trick is to have great platforms without creating bureaucracy and to build great teams for speed."

If you create a strong culture and enough teams that can get stuff done, Dimon argued that you get a company with its own neural network. People have health connections enabled by technology. The network of people and technology needs "to perform like a well-functioning sports team."