The Federal Reserve is "obsessed" with AI, but dares not make another "Greenspan-style gamble."

Federal Reserve officials are increasingly focused on the potential of artificial intelligence to transform the economy, but remain cautious about whether it has triggered a productivity revolution.

Although AI investment is driving a significant portion of US economic growth, central bank policymakers are still in the "too early to judge" stage and are reluctant to make major policy bets as they did during the Internet boom of the 1990s. At that time, then-Fed Chairman Alan Greenspan believed that innovation could promote faster economic growth without triggering inflation, and used this as the basis for maintaining low interest rates.

US Treasury Secretary Scott Bessent told CNBC last month that the implementation of AI in the first half of 2026 will "really begin to have an impact on productivity." He believes the next Fed Chair should keep an "open mind" about the possibility of an AI-driven productivity boom and avoid repeating the mistakes that stifled the Internet boom.

Of the five Fed Chair candidates, four have recently expressed support for the AI productivity argument. Trump National Economic Council Director Kevin Hassett said AI is raising worker productivity "at an astonishing pace," while BlackRock executive Rick Rieder stated "we are in the midst of a productivity revolution."

This debate is unfolding at a critical moment for the Federal Reserve. Chairman Powell’s term ends in six months, and inflation remains above target, creating divisions over interest rate policy. The potential impacts of AI on the labor market add further complexity to policy-making.

Productivity data shows positive signals

Recent research from the St. Louis Fed found that since the launch of ChatGPT three years ago, generative AI may have increased labor productivity by 1.3%. Researchers surveyed workers regularly to ask how much work time was saved using AI, and discovered a significant link between higher AI adoption rates in an industry and increased productivity.

Alexander Bick, one of the study’s co-authors, said: "What surprised me is just how clearly this signal appears at the industry level. The correlation is already there."

Bloomberg Economics’ chief US economist Anna Wong noted that a productivity boom is "a dream come true" for central bankers, and "a unicorn" for macroeconomists, appearing only every few decades. She believes macro-level evidence is still unclear, but micro-level evidence is starting to emerge.

Company-level practices also support this view. Peter Capuciati, CEO of HVAC equipment AI service provider Bluon Inc., estimates their AI tools can save technicians up to eight hours of work per week. Currently, about 160,000 technicians use the free version, and 13,000 pay for the full service.

Data quality limits accurate judgment

Kristina McElheran, a University of Toronto scholar studying AI and the future of work, points out that the lack of "granular, high-fidelity data on corporate AI usage" is the fundamental problem being faced. Many striking studies are based on "real data issues."

"We are flying blind into this AI revolution," McElheran said. "We don't have the statistics that policymakers need, nor those that managers need." Modelers can only "take past trends and try to apply them to things happening quickly right now."

This data dilemma is making Fed officials more cautious in policy decisions. While technology shifts usually take years to show results in the economy and data, the central bank is under pressure to make decisions at a critical time.

Currently, Fed Governor Christopher Waller has made relatively cautious remarks, saying he has "no doubt" AI will promote economic development and he "hopes" to see sustained productivity growth. Vice Chair for supervision Michelle Bowman discusses AI more often from the perspective of regulatory work.

Job market shocks raise new concerns

The double-edged nature of AI technology adds complexity to policymaking. While technological advances typically boost productivity, they can also impact the job market. The Fed's recent Beige Book survey shows that AI is dampening hiring demand, especially for entry-level positions.

Capital Economics research points out that the information technology sector, an early adopter of AI, is contributing a larger share to US economic growth even as its employment levels shrink—both evidence of improved productivity and a reflection of the risks of technological spread.

Julia Coronado, founder of Macropolicy Perspectives LLC, noted that unlike companies during the 1990s Internet boom who used innovation to expand employment, today’s firms are more likely to use AI to reduce workforce size.

Northwestern University professor and author of “The Rise and Fall of American Growth” Robert Gordon said he is willing "to shift away from my usual productivity pessimism." The 85-year-old scholar believes AI may bring faster growth than in previous decades, "about a moderate 2%, probably not reaching 3% for a long time, maybe one or two years."

But Gordon also worries the coming era could contain a darker side, as AI might create "a series of new social problems accompanying white-collar unemployment," and "in a society where a white-collar job is every young person’s aspiration," this will be a severe challenge.

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