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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsAI could eventually lift productivity and ease inflation, but policymakers cannot assume those gains will arrive before AI-related investment and optimism boost demand. That timing problem is central to how AI may affect monetary policy. The specific title “Monetary Policy in the Age of AI” is not verified as a speech by Federal Reserve Governor Christopher J. Waller, so the analysis below draws on separate remarks by St. Louis Fed President Alberto Musalem rather than attributing his views to Waller.
Why AI presents a two-sided problem for monetary policy
Monetary policy responds to the economy as it is unfolding: demand, prices, employment and the outlook for inflation. AI may affect both the economy’s capacity to produce goods and services and the amount people and businesses want to spend. Those effects can arrive at different times, making it difficult to infer from current activity what AI will mean for inflation later.
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In remarks on May 28, 2026, St. Louis Fed President Alberto Musalem described this tension. He said: “To date, the data are inconclusive about aggregate productivity being in a sustained higher growth regime.” That is a statement about the evidence available to Musalem at the time, not a conclusion by Waller and not proof that AI will have no productivity effect.
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How AI-driven productivity could ease inflation
If AI helps workers and businesses produce more with the same inputs, productivity rises. Over time, stronger productivity can expand the economy’s productive capacity: firms may be able to meet a given level of demand with less pressure on labor, equipment or other resources. If supply grows faster, that can reduce inflationary pressure relative to a path with weaker productivity growth.
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The timing and scale matter. The potential supply benefit depends on AI being adopted and used effectively across enough of the economy to raise measured productivity. A promising technology, individual company gains or rising investment do not by themselves establish a durable increase in aggregate productivity. Musalem’s assessment was that aggregate data had not yet shown a sustained higher-growth regime.
Why demand can rise before productivity gains are visible
Expected future benefits can affect spending now. Businesses may invest in AI-related equipment, software or organizational changes in anticipation of later efficiencies. Households or investors may also respond to expected gains in income or wealth. That additional investment and spending can raise current demand even while economy-wide productivity gains remain uncertain or have yet to materialize.
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This creates an important mismatch: demand effects can appear before the corresponding expansion in supply. If spending grows faster than productive capacity in the near term, it can add to price pressure. If productivity gains later broaden and persist, the supply response may ease that pressure. Neither outcome follows automatically from AI enthusiasm alone.
What the timing problem means for policy
Policymakers must weigh observable current conditions against uncertain future changes. Current investment, demand and inflation data can show pressure building before official productivity measures capture possible AI benefits. Conversely, early productivity gains may be difficult to distinguish from ordinary fluctuations until they persist across the broader economy.
Musalem argued that, in the circumstances he described, it would be risky to rely on future productivity growth to resolve current inflation. This is Musalem’s judgment, not a verified Waller position under the title in this article. The practical point is that a central bank cannot treat a forecast of future supply gains as if those gains were already established in the data.
For readers, the key distinction is between the possibility that AI will raise long-run productive capacity and evidence that it is already doing so at an aggregate, sustained rate. Monetary policy has to navigate the interval between those two: AI-related demand may be visible while the supply benefits remain uncertain.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Did Christopher Waller give a speech with this exact title?
The Federal Reserve Board’s 2026 speech archive lists Waller remarks including “Operationalizing AI at the Federal Reserve,” delivered on February 24, 2026, but does not list a speech titled “Monetary Policy in the Age of AI.” A separate bibliographic listing of Christopher Waller’s speeches also does not establish that exact title.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchThe available records therefore do not confirm the event, date, venue, text or argument behind “Fed’s Waller on Monetary Policy in the Age of AI.” It may be an editorial heading rather than the title of a published speech. Musalem’s May 2026 remarks provide relevant Federal Reserve context, but his views should not be presented as Waller’s.
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What the Federal Reserve’s own AI figures do—and do not—show
Musalem reported that 86% of Federal Reserve Bank of St. Louis staff had been trained to use AI and 77% used an approved AI tool in their work. These figures describe that Reserve Bank’s staff in 2026. They do not measure adoption across the U.S. workforce, the economy-wide productivity effects of AI, or the impact of AI on inflation.
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