Federal Reserve governor warns: Monetary policy may not be able to address unemployment caused by AI

Federal Reserve Board member Lisa Cook issued a warning on Tuesday that an AI-driven restructuring of the labor market could put monetary policy in a dilemma—rate cuts would neither effectively address structural unemployment nor might push up inflation. This assessment marks a deepening internal discussion within the Fed about the economic impact of AI.

Speaking at the annual policy conference of the National Association for Business Economics, Cook said, “We seem to be approaching the most profound restructuring of employment in generations,” and during the transitional phase of economic transformation, “Job replacement may precede job creation, unemployment may rise, and labor force participation may decline.”

Cook believes that AI has triggered generational shifts in the U.S. labor market and could lead to rising unemployment, which the Fed may be unable to address through rate cuts. She warned:

“During these periods of productivity booms, rising unemployment does not necessarily mean there is more slack in the economy. As we address AI-driven unemployment, our conventional demand-side monetary policy may not work without increasing inflationary pressure.”

Cook’s comments came at a sensitive time in the market. Last weekend, a firm called Citrini Research published what amounted to a ‘2028 Doomsday Prophecy’ report detailing the potential shock risks of AI in several global economic sectors, triggering a slump in U.S. software, delivery, payment, and financial stocks on Monday.

Another Fed governor, Christopher Waller, who also spoke on Tuesday, holds a view different from Citrini’s. At another event, he said Citrini’s report “overstates the potential impact of AI on employment” and stressed, “AI is a tool; it does not replace us as humans.”

Monetary policy faces a new dilemma between inflation and unemployment

The core point in Cook’s argument is that unemployment caused by AI is essentially different from conventional cyclical unemployment—the former arises from structural adjustments rather than insufficient aggregate demand, which greatly undermines the effectiveness of monetary policy tools.

She clearly pointed out that when productivity is rising and economic growth remains strong, increased unemployment due to labor market “re-shuffling” does not indicate economic overcapacity. In such circumstances, if the Fed uses traditional demand-side tools to respond, it may fail to genuinely resolve the employment problem and at the same time, inadvertently push up inflation.

Cook said: “Monetary policymakers will face trade-offs between unemployment and inflation…Education, workforce training, and other non-monetary policy measures may be better suited to address these challenges more directly.”

Cook also emphasized that it is currently impossible to determine the exact trajectory and intensity of this round of labor market restructuring. Early signals are already showing in the jobs market—demand for workers in professions where AI has penetrated deeply, such as programming, has noticeably decreased, and the unemployment rate of recent college graduates has been steadily rising over recent years, partly because some employers are introducing AI into work previously handled by entry-level employees.

However, she also noted, “Overall unemployment remains at a low 4.3%, and recent layoff indicators are still mild.”

AI may first push up, then push down the neutral interest rate

Aside from the job market, Cook offered contrasting judgments about AI’s short-term and long-term impacts on the neutral rate, another focus of her speech.

She stated that before the full productivity dividend is realized, massive AI-related commercial investments—including data centers and chip purchases—are boosting aggregate demand, “The current neutral rate may be higher than pre-pandemic levels.”

This judgment echoes views of some Fed officials, who have recently suggested that an AI-driven productivity boom may lift the neutral rate.

But Cook also flagged the risk of this logic reversing. She observed:

“When AI’s productivity gains are more fully realized, or if labor market restructuring exacerbates income inequality and enables wealthy consumers to gain a larger share of income, this trend may reverse, and the neutral rate may fall if other factors remain unchanged.”

Cook added in post-conference panel discussions that AI’s full impact may take five to ten years to be reflected in productivity data across the economy.

She also said the Fed has included AI in its forecasting models, including its potential impact on the neutral rate and the effect of data center investments on economic growth.

Fed’s internal AI policy discussions increasingly deepen

Cook’s remarks are the latest in a recent series of statements by Fed policymakers about AI’s implications for monetary policy, reflecting that this topic has moved from a fringe issue to a central area of focus within the Fed’s decision-making circles.

After three consecutive 25-basis-point rate cuts, the Fed decided at its most recent FOMC meeting in January this year to keep policy rates unchanged, citing signs of stabilization in the labor market.

Futures market pricing shows investors currently expect the Fed to resume rate cuts no sooner than mid-year. Cook did not comment on the short-term direction of monetary policy in this speech, but she referred to the latest labor market data released after the January meeting, stating the data reinforced the judgment of market stabilization.

Before joining the Fed, Cook herself had conducted over twenty years of research in innovation economics, applying machine learning methods in her work. Thus, her speech carried both policy and academic dimensions.

In her opening remarks, she said that while remaining cautious, she is optimistic about AI’s long-term prospects, believing AI technology will ultimately drive product and process innovation, “making our lives better.”

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