In a high-profile fireside chat at the Federal Reserve in Washington, DC, OpenAI CEO Sam Altman sat down with Fed Vice Chair Michelle Bowman to sketch a sweeping vision of artificial intelligence and its implications for finance, employment, and society at large. The conversation, at the Fed’s Integrated Review of the Capital Framework for Large Banks Conference, covered the acceleration of AI adoption, productivity booms, looming risks, and why Altman thinks banks—and regulators—must rethink their approach to innovation.
Altman recounted the astonishing velocity of AI development and acceptance. “Only five years ago, AI was still thought of as something that was in the distant future,” he remarked, highlighting the dramatic changes since ChatGPT’s launch in November 2022. Since then, AI has leaped from niche to necessity, with new models achieving “gold-level performance” in tasks once reserved for elite human experts.
Productivity stories are pouring in from scientists and engineers: “We’re now hearing from scientists saying they’re two, three times more productive. We’re hearing from computer programmers that say they’re 10 times more productive. That’s completely changed what it means to write software.”
Altman captured the phenomena with a striking phrase: “It does in fact look like we’re about to deliver on ‘intelligence too cheap to meter.’ We’ve been able to drive down the cost of each unit of intelligence by more than a factor of 10 each year for the last five years.” He described a personal anecdote where a coding task, once days of work for an expert, was now solved by AI in five minutes for “less than a dollar’s worth of compute tokens.”
AI will make the phrase ‘AI company’ obsolete
Bowman, addressing a room of industry leaders, pressed Altman on the potential for AI to remake productivity in finance and beyond. Altman compared AI’s societal impact to the invention of the transistor: “The value sort of diffused throughout all of society as a massive productivity win.” He predicted the phrase “AI company” would soon sound outmoded, as every product and service would be expected to integrate intelligence by default.
Early adopters in finance are already deep in experimentation. Despite initial skepticism, institutions like Morgan Stanley and Bank of New York have embraced AI for critical functions. “Some of our biggest early enterprise partners turned out to be financial institutions,” Altman said, noting that they’ve figured out how to use the technology for critical processes.
On job disruption, Altman was candid about the uncertainty: “No one knows what happens next.” While predicting that some classes of jobs will vanish and others will emerge, he insisted that increased productivity historically leads to more, not less, human aspiration and creativity.
“There are cases where entire classes of jobs will go away. There are entirely new classes of jobs that will come.” He said he thinks that process will look like “most of history,” where humans and economies have adapted to the tools that technology creates.
“It turns out people seem to want unlimited stuff. Have a huge desire to express their creativity and be useful to people,” Altman continued. He added he’s “still waiting for that promise from the industrial revolution that we only had to work four hours a week and got to play on the beach and hang out with our kids,” he said, seemingly referring not to 19th-century forecasts on the future of work but 20th century economist John Maynard Keynes’ famous predictions about the future of work.
The panel did not wade into Keynes’ prediction that a 15-hour workweek would be achieved by the time of Keynes’ hypothetical grandchildren, as they would have been alive during the period leading up to 2030, almost exactly the current time. The conversation also didn’t expand into the subject of tariffs, protectionism or outsourcing, as the history of the decline of American manufacturing and the “China shock” of the 21st century suggest history is not a linear line in technological and economic disruption.
A future full of AI risk, even ‘fraud’
Altman also issued blunt warnings on the risks of AI, particularly synthetic fraud and impersonation, noting, “AI has fully defeated most of the ways that people authenticate currently other than passwords.” He urged banks and society to move away from voice- or image-only authentication methods and to prepare for new waves of cybercrime.
He described three broad risk categories: bad actors exploiting superintelligence, loss-of-control incidents (as sci-fi warns), and a subtler threat where society becomes so dependent on AI that human oversight, decision-making, and even government governance could degrade. “Emotional over-reliance,” especially among youth, is already emerging as a concern.
Throughout the conversation, Altman urged governments and businesses to move quickly but mindfully in adopting AI, stressing the importance of regulation that enables innovation rather than stifling it. He drew parallels to historical anxieties over calculators and Google, pointing out that such tools ultimately allowed people to focus on higher-level skills.
He also described how AI could become a global equalizer, especially in developing markets with limited access to professionals: “In a lot of the developing world, the alternative to a ChatGPT doctor is not a real doctor, it’s nothing at all, and then you’d definitely rather have this.”
In closing, Altman highlighted the rapid shift to advanced “reasoning models” in AI and invited financial leaders and government to embrace this new wave. “Government has got to embrace this technology, and we’ll be able to do everything better.”
For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing.
