Jamie Dimon leads new industry push to manage AI risks across banking

Jamie Dimon leads new industry push to manage AI risks across banking
JPMorgan's CEO is rallying corporate America around shared AI safeguards as banks report widening use of the technology in daily operations.
AUG 05, 2026

Jamie Dimon is stepping up efforts to unite corporate America around a common approach to artificial intelligence risk, according to two people familiar with the matter, as banks increasingly weave AI into daily operations from fraud detection to advisor productivity tools.

The JPMorgan Chase chief executive has personally called counterparts at major banks and technology firms, inviting them to join a US-focused coalition built out of the Alliance for Critical Infrastructure, a group JPMorgan helped establish alongside Mastercard and Berkshire Hathaway Energy, Reuters reported.

Outreach efforts that began in July have already drawn more than 40 companies spanning banking, energy, utilities, telecommunications and transportation, according to the news agency's sources.

A coalition for the AI era

The effort is meant to give companies a shared understanding of how AI is being deployed, what risks it introduces, and what safeguards are needed, while coordinating with federal regulators on those questions. Recent cyberattacks on water infrastructure in Minnesota and other states have added urgency to the push for more information-sharing across sectors, sources told Reuters.

Dimon has been blunt about the stakes. Discussing the risks tied to advanced AI systems, he said in July that "you're giving ballistic missiles to individuals with Mythos," referring to Anthropic's advanced AI model as he underscored the need for guardrails alongside access to the world's most powerful AI tools.

The coalition's work is separate from a parallel industry effort among banks to stress-test frontier AI models for security vulnerabilities.

Concerns around AI risks are also top of mind among compliance officers at RIAs, as more than half of respondents in the most recent Investment Management Compliance Testing Survey cited AI and predictive analytics as the "hottest" topics ahead of money laundering and cybersecurity.

Banks moving ahead of the policy conversation

While the coalition-building continues, the operational reality inside major banks has moved quickly. As reported by CIO Dive, Bank of America CEO Brian Moynihan told investors during the bank's second-quarter earnings call that more than 200,000 employees now use AI-enabled tools, generating over 400,000 prompts a day across productivity, coding and client-preparation use cases. The bank has more than 300 approved AI use cases, including 114 generative AI applications, with 34 fully implemented, according to the outlet.

Separately, Citigroup CEO Jane Fraser said nearly nine in ten of the bank's employees are now using its AI tools, crediting the technology with speeding up product development alongside productivity gains.

At JPMorgan, executives point to nearly 1,000 live AI use cases spanning risk management, fraud prevention, marketing and document review. Dimon, however, has downplayed the idea that AI will meaningfully lift margins in the near term, saying the bank's investors "don't uniquely benefit from AI" as he expects customers rather than shareholders will capture much of the benefit.

That skepticism about near-term profit gains lines up with independent survey data. A D.A. Davidson survey of bank executives, cited by S&P Global and other online sources, found that institutions expect AI's expense benefits to run roughly twice the size of any revenue lift over the next two to three years, with average projected expense reductions of 4.5% to 5% against revenue growth of just 2.5% to 3%.

Larger banks, those with more than $50 billion in assets, expect the biggest payoff, projecting a 5.6% expense cut against 3.1% revenue growth, the survey found. Notably, just 11% of surveyed banks said those cost savings are actually measurable today, a concrete reminder that AI's return on investment remains difficult to quantify even as adoption accelerates.

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