Federal Reserve Board Member Warns: Monetary Policy May Be Unable to Address AI-Triggered Unemployment Wave

Federal Reserve Board Governor Lisa Cook warned on Tuesday that AI-driven labor market restructuring could put monetary policy in a dilemma—cutting interest rates may neither effectively address structural unemployment nor prevent inflation from rising. This marks a deepening internal discussion within the Fed about AI’s economic impact.

Speaking at the annual policy conference of the National Business Economics Association, Cook said, “We seem to be approaching the most profound employment restructuring in decades.” During this economic transition, “job displacement may precede job creation, leading to higher unemployment and potentially lower labor force participation.”

Cook believes that AI has triggered a generational shift in the U.S. labor market and may cause unemployment to rise, which the Fed might be unable to counteract with rate cuts. She warned:

“During this productivity boom, rising unemployment does not necessarily mean excess capacity in the economy. Therefore, conventional demand-side monetary policy may not be effective in addressing AI-induced unemployment without triggering upward inflation pressures.”

Cook’s comments came at a sensitive market moment. Last weekend, Citrini Research released a report dubbed the “2028 Doomsday Prediction,” detailing potential risks of AI impacts across various global economic sectors, which led to sharp declines in tech, food delivery, payments, and financial stocks in the U.S. stock market this Monday.

Another Fed official, Christopher Waller, who also spoke on Tuesday, held a different view from Citrini. He stated that Citrini’s report “overstates the potential impact of AI on employment” and emphasized, “AI is a tool; it will not replace us as human beings.”

Monetary Policy Faces New Dilemmas of Inflation and Unemployment

Cook’s core argument is that AI-induced unemployment differs fundamentally from traditional cyclical unemployment. The former stems from structural adjustments rather than insufficient aggregate demand, which diminishes the effectiveness of monetary policy tools.

She clearly pointed out that when productivity continues to improve and economic growth remains strong, increased unemployment due to labor market “restructuring” does not indicate excess capacity in the economy. In such cases, if the Fed relies on traditional demand-side tools, it may fail to substantially improve employment while additionally pushing up inflation.

Cook said, “Policy makers will face trade-offs between unemployment and inflation… Education, workforce training, and other non-monetary measures may be more targeted ways to address these challenges.”

She also emphasized that it is still uncertain how this labor market transformation will unfold and its intensity. Early signals include a noticeable decline in demand for jobs in fields most affected by AI, such as programming, and a rising unemployment rate among recent college graduates over the past few years, partly because some employers are integrating AI into roles previously handled by entry-level workers.

However, she also noted that “the overall unemployment rate remains low at 4.3%, and recent layoffs have been moderate.”

AI May First Push Up, Then Lower Neutral Interest Rates

Beyond employment, Cook offered contrasting views on AI’s short- and long-term effects on the neutral interest rate, another key policy focus of her speech.

She stated that before the full realization of productivity gains, large-scale AI-related business investments—including data centers and chip procurement—are boosting aggregate demand, and “the current neutral rate could be higher than pre-pandemic levels.”

This view aligns with some Fed officials who have recently suggested that AI-driven productivity booms could raise the neutral rate.

But Cook also warned of the risks of this logic reversing. She pointed out:

“When AI’s productivity benefits are more fully realized, or if labor market shifts lead to increased income inequality—giving wealthier consumers a larger share of income—this trend could reverse, and the neutral rate would decline, all else being equal.”

In a post-meeting discussion, Cook added that the impact of AI might take five to ten years to fully appear in macroeconomic productivity statistics.

She also mentioned that the Fed has incorporated AI into its forecasting models, including its potential effects on the neutral rate and the contribution of data center investments to economic growth.

Internal Fed Discussions on AI Policy Deepen

Cook’s speech is the latest example of recent intensive discussions among Fed policymakers regarding the implications of AI for monetary policy, reflecting that this topic has moved from a peripheral issue to a core consideration at the decision-making level.

After three consecutive rate cuts of 25 basis points, the Fed’s most recent January FOMC meeting decided to hold rates steady, citing signs of labor market stabilization.

Futures markets currently price in the earliest rate cuts around mid-year. Cook did not comment on the short-term policy trajectory but noted that recent labor market data, including the latest figures released after the January meeting, reinforce the market’s view of stabilization.

Prior to joining the Fed, Cook spent over twenty years researching innovative economics, employing machine learning methods in her work. Her speech thus combines policy and academic perspectives.

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

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