The San Francisco Fed president sees AI influencing monetary policy decisions, though she isn't ready to call it an inflation driver yet
San Francisco Federal Reserve Bank President Mary Daly says artificial intelligence will shape monetary policy decisions in the near and medium term.
She is not saying AI is about to set interest rates. She is saying the technology is now part of the backdrop that policymakers have to account for.
What Daly has actually said about AI
Daly’s thinking on AI has developed across several public appearances. The most detailed came on February 17, 2026, when she spoke at the Silicon Valley Leadership Group.
The speech carried a title that reads like a TED Talk with a policy minor: “The AI Moment? Possibilities, Productivity, and Policy.”
Her core point was measured. Macroeconomic studies so far show limited evidence that AI is delivering immediate productivity gains.
Still, she said the integration of AI is expected to transform productivity and economic growth over time.
Daly also argued that the Fed needs to look past aggregate data to understand what AI might do. She pointed toward disaggregated information as a better way to gauge the technology’s potential impact.
By June 2026, Daly had sharpened the timeline. She said AI could become deflationary over a 5- to 10-year window.
But she also said the technology poses no immediate concern for monetary policy set on a 12-month horizon. AI is not, in her view, a current driver of inflation.
That distinction matters. The Fed makes rate decisions with roughly a year ahead in mind, so a force that plays out over five to ten years sits outside the immediate decision window, even if it shapes the longer conversation.
The ‘slightly restrictive’ stance and the AI wildcard
In October 2026, Daly described US monetary policy as “slightly restrictive.”
She also flagged that uncertainty around AI-driven investments makes it harder to forecast where policy goes next. Companies pouring money into AI infrastructure creates demand today, while the productivity benefits remain a promise for tomorrow.
This is the dual nature of AI’s economic footprint, as Daly has framed it. In the short run, spending on AI can bolster demand. In the longer run, it could raise productivity and push prices lower.
Daly has also been clear about where AI sits inside the Fed itself. The central bank uses AI for operational tasks such as coding and improving research efficiency.
It does not, however, use AI for monetary policy formulation or economic forecasting decisions.
The Greenspan playbook
Daly has drawn parallels between today’s AI debate and the technology revolution of the 1990s under former Fed Chair Alan Greenspan.
During that era, policymakers had to decide whether a wave of new technology was quietly changing how fast the economy could grow without overheating.
Daly’s emphasis on disaggregated data echoes that approach. The idea is to look for early signals in the details before they show up clearly in the headline statistics.
What this means for markets and policy watchers
For investors, Daly’s comments point to a patient Fed rather than one rushing to rewrite its framework around AI. If AI is not a near-term inflation driver, it is unlikely to be the main reason for rate moves over the next year.
The longer view is where things get more complex. If AI does become deflationary over a 5- to 10-year window, as Daly has suggested it could, that may eventually change how the Fed thinks about growth, inflation and the appropriate level of rates.
Heavy AI investment could keep demand firm in the meantime, even as the promised productivity gains take their time arriving. That gap between spending now and benefits later is exactly what complicates forecasting, and explains why Daly keeps returning to the theme of uncertainty rather than offering firm predictions.
For now, Daly’s message is one of watchful curiosity. AI is on the agenda and shaping the thinking, but it has not yet earned a seat at the decision table.
