Federal Reserve struggles to predict AI's impact on jobs and inflation as divide emerges

Fed races to adapt to AI promises and pitfalls for jobs, inflation

WASHINGTON, March 2 (Reuters) - U.S. Federal Reserve officials who have largely accepted that artificial intelligence will lead to dramatic shifts in the economy are now struggling to understand the pace and extent of what's to come, with a divide emerging over its potential to impact the labor market and prices. The announcement by tech firm Block on Thursday that it would shed 40% of its workers, roughly 4,000 people, because "something has changed" in how it uses labor due to AI, highlighted the stakes. Rising layoffs would traditionally lean central bankers towards looser monetary policy. The AI transition, though, has raised a different response, with officials saying higher unemployment rates may be par for the course ahead, with displaced workers taking longer to find new jobs and the higher capital returns and wages for those still working keeping upward pressure on inflation. "We're in the part of the cycle where this is a positive, real shock, but most of it is in the form of positive real income and very little disinflation," with stock gains padding some households' wealth, and massive capital investment straining electricity and building costs in some areas, Adam Posen, president of the Peterson Institute for International Economics,said in a discussion about inflation, opens new tab, estimating U.S. price pressures would build from here. Those seeing AI as a near-term disinflationary force "have got it exactly wrong." WARSH READY TO BANK ON AI DISINFLATION? That group includes Fed chair nominee Kevin Warsh, who feels interest rates should fall in part to account for AI-driven productivity gains holding down inflation. Warsh, who must still be formally nominated and confirmed by the Senate, argued in a November Wall Street Journal op-ed that AI is "a significant disinflationary force, increasing productivity and bolstering American competitiveness," and could be best accommodated by the Fed with lower rates. Warsh's narrative, which he casts as a forward-looking stance similar to former Fed Chair Alan Greenspan's in the mid-1990s, has been met by growing caution among Fed policymakers about how fast AI will translate into staffing practices and whether the historical rule of thumb will hold that new technologies displace jobs but ultimately create even more. Citrini Research's thought exercise last week, opens new tab, warning of a jobs apocalypse, triggered a brief but significant stock selloff, a sign of how unsettled investors and perhaps the wider public have become about AI. The announcement by Block, owner of fintech services Square and Cash App, seemed to show its disruptive potential: Unlike prior automation developments that mostly impacted blue-collar production jobs, AI may be suited to do white-collar tasks like coding or data analysis. Coding assistants might well improve employee productivity, but Block CEO Jack Dorsey said AI "paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. And that's accelerating rapidly." A growing body of research has consistently concluded that AI can perform a wide variety of tasks, including many in the knowledge sectors that have been a focus for high schools, colleges and local chambers of commerce wanting to future-proof the labor force. A 2024 paper by Brookings Institution analysts found more than 30% of U.S. workers, opens new tab could see half of their job tasks "disrupted," percentages that have likely grown. FED EFFORTS GATHERING STEAM The Fed is trying to keep pace. An AI-driven count of Fed research articles and policymaker speeches about AI, machine learning and related topics shows few before ChatGPT's release in late 2022. That rose to five in 2023, around 17 last year, and 14 already this year, a much faster pace. Minutes of the Fed's January meeting showed a fulsome discussion of productivity and AI, including what it might mean for monetary policy, and at least five policymakers spoke on the topic last month. As a group, they are far from banking on AI as a reason to cut rates anytime soon. They agree productivity seems to be moving higher, but aren't ready to credit AI as opposed to more mundane efficiencies achieved during pandemic-era labor shortages. Even if the "baton" of productivity is now being passed, policymakers seem to be leaning toward a view that AI will cause structurally higher unemployment, not easily offset by lowering rates without risking higher inflation. Underpinning the Fed's framework is a long-run "natural" unemployment rate, currently thought to be around 4.2%, below which inflation pressures build. "If AI continues to raise productivity, economic growth could remain strong, even as churn in the labor market leads to an increase in unemployment. In a productivity boom such as this, a rise in unemployment may not indicate increased slack. As such, our normal demand-side monetary policy may not be able to ameliorate an AI-caused unemployment spell without also increasing inflationary pressure," Fed Governor Lisa Cook said last month, opens new tab, remarks echoed by several colleagues. The issue is hardly settled. Evercore ISI Vice Chair Krishna Guha sees a loss of worker bargaining power as a reason why the natural unemployment rate will fall as employees become willing to stay in jobs and accept lower wage increases, putting downward pressure on inflation - an argument that reaches conclusions similar to those of Warsh in terms of cutting interest rates but for somewhat different reasons. But the public comments from Fed officials have painted a more complex picture: jobs under pressure for some workers, new productive potential for others, wealth gains fueling consumption in some households, resource constraints during the AI buildout, and high expected investment returns likely to raise underlying interest rates. "There are lots of forecasts about both the rollout of AI, the effectiveness of AI, the energy efficiency of AI, the labor market implications of AI, and the only thing you know for sure is those forecasts are going to be wrong," Richmond Fed President Tom Barkin said last week. "Whether they are going to be too optimistic or too pessimistic you'll have to sort out as you go." Reporting by Howard Schneider; Editing by Dan Burns and Andrea Ricci Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Artificial Intelligence Howard Schneider Thomson Reuters Covers the U.S. Federal Reserve, monetary policy and the economy, a graduate of the University of Maryland and Johns Hopkins University with previous experience as a foreign correspondent, economics reporter and on the local staff of the Washington Post.

Fed's Waller says central bank deploying AI tech cautiously

Feb 24 (Reuters) - Federal Reserve Governor Christopher Waller said Tuesday the U.S. central bank is carefully moving to adopt artificial intelligence technology in a system-wide approach. "We cannot approach AI casually," and "as a central bank, we hold ourselves to a high standard" when using the technology, Waller said at a conference held by the Federal Reserve Bank of Boston. For the Fed and AI usage, "that means clear guardrails on how and where it's used, strong information-security controls, rigorous model validation, human accountability for decisions, and ongoing evaluation as the technology evolves," with innovation and risk management standing together as complementary priorities, the Fed official said. Waller did not comment on the economic and monetary policy outlook in his prepared remarks. Waller said that despite the Fed being a highly decentralized organization, it is taking a more unified approach to implementing AI technology. "We're moving as one system, with shared direction and alignment," Waller said. And in terms of deciding what to deploy the technology for, "we start with the problem to be solved and the business need, then apply the right capability" from the suite of available AI technology. Reporting by Michael S. Derby; Editing by Chizu Nomiyama Our Standards: The Thomson Reuters Trust Principles., opens new tab

Federal Reserve Powers Internal Operations With New General-Purpose AI | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. In a speech delivered at the Federal Reserve Bank of Boston 2026 Technology-Enabled Disruption Conference in Boston, Waller said the Fed built an "innovation practice" that encompasses the entire Federal Reserve System so that technologies can be tested and implemented more efficiently than if that work were to be done at each of its banks. In the case of AI, the Fed developed a general-purpose AI platform to be used by all Reserve bank employees. "Our approach is intentionally business-led and AI-enabled," Waller said. "We start with the problem to be solved and the business need, then apply the right capability from across the AI stack. That discipline helps us deliver real business value while avoiding unnecessary complexity and cost." With the general-purpose AI for all employees, the Fed aims to provide a digital assistant that can do things such as drafting, summarizing and analyzing information so employees can focus on higher value activities. In practice, Fed staff use this tool for tasks such as generating key themes from background materials ahead of a meeting and summarizing and prioritizing emails and documents that arrived while they were on vacation. "In both cases, the tool handles the volume and the first pass," Waller said. "The human makes the decisions." Another key focus of the Fed's deployment of AI is in software development. Coding assistants accelerate many of the tasks involved in software development, enabling developers to focus on the security and quality that are critical for an institution like the Federal Reserve. "At the Fed, we're already seeing strong early uptake -- with hundreds of developers adopting these tools quickly -- which tells us this capability is meeting a real need," Waller said. The third focus of the Fed's initiative is embedding AI into existing platforms rather than asking teams to adopt entirely new tools. This enables the Fed to make improvements without creating fragmented solutions. "Given how quickly the technology is evolving, consuming AI through vendor platforms allows us to benefit from ongoing improvements, rather than building and maintaining tools that can become costly and stable," Waller said. Waller delivered his remarks on the same day Federal Reserve Governor Lisa Cook said in a speech that rapid advances in AI could pose new challenges for the central bank's traditional tools as it fundamentally reshapes the U.S. economy. The PYMNTS Intelligence report "Agentic AI Breaks Out of the Sandbox" found that among chief product officers at U.S. enterprise level firms, as of November, 11.7% are already using agentic AI and another 11.7% are piloting/testing the technology. Three months earlier, in August, those figures stood at 1.7%.

Fed races to adapt to AI promises and pitfalls for jobs, inflation

WASHINGTON, March 2 (Reuters) - U.S. Federal Reserve officials who have largely accepted that artificial intelligence will lead to dramatic shifts in the economy are now struggling to understand the pace and extent of what's to come, with a divide emerging over its potential to impact the labor market and prices. The announcement by tech firm Block on Thursday that it would shed 40% of its workers, roughly 4,000 people, because "something has changed" in how it uses labor due to AI, highlighted the stakes. Rising layoffs would traditionally lean central bankers towards looser monetary policy. The AI transition, though, has raised a different response, with officials saying higher unemployment rates may be par for the course ahead, with displaced workers taking longer to find new jobs and the higher capital returns and wages for those still working keeping upward pressure on inflation. "We're in the part of the cycle where this is a positive, real shock, but most of it is in the form of positive real income and very little disinflation," with stock gains padding some households' wealth, and massive capital investment straining electricity and building costs in some areas, Adam Posen, president of the Peterson Institute for International Economics, said in a discussion about inflation, estimating U.S. price pressures would build from here. Those seeing AI as a near-term disinflationary force "have got it exactly wrong." WARSH READY TO BANK ON AI DISINFLATION? That group includes Fed chair nominee Kevin Warsh, who feels interest rates should fall in part to account for AI-driven productivity gains holding down inflation. Warsh, who must still be formally nominated and confirmed by the Senate, argued in a November Wall Street Journal op-ed that AI is "a significant disinflationary force, increasing productivity and bolstering American competitiveness," and could be best accommodated by the Fed with lower rates. Warsh's narrative, which he casts as a forward-looking stance similar to former Fed Chair Alan Greenspan's in the mid-1990s, has been met by growing caution among Fed policymakers about how fast AI will translate into staffing practices and whether the historical rule of thumb will hold that new technologies displace jobs but ultimately create even more. Citrini Research's thought exercise last week, warning of a jobs apocalypse, triggered a brief but significant stock selloff, a sign of how unsettled investors and perhaps the wider public have become about AI. The announcement by Block, owner of fintech services Square and Cash App, seemed to show its disruptive potential: Unlike prior automation developments that mostly impacted blue-collar production jobs, AI may be suited to do white-collar tasks like coding or data analysis. Coding assistants might well improve employee productivity, but Block CEO Jack Dorsey said AI "paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. And that's accelerating rapidly." A growing body of research has consistently concluded that AI can perform a wide variety of tasks, including many in the knowledge sectors that have been a focus for high schools, colleges and local chambers of commerce wanting to future-proof the labor force. A 2024 paper by Brookings Institution analysts found more than 30% of U.S. workers could see half of their job tasks "disrupted," percentages that have likely grown. FED EFFORTS GATHERING STEAM The Fed is trying to keep pace. An AI-driven count of Fed research articles and policymaker speeches about AI, machine learning and related topics shows few before ChatGPT's release in late 2022. That rose to five in 2023, around 17 last year, and 14 already this year, a much faster pace. Minutes of the Fed's January meeting showed a fulsome discussion of productivity and AI, including what it might mean for monetary policy, and at least five policymakers spoke on the topic last month. As a group, they are far from banking on AI as a reason to cut rates anytime soon. They agree productivity seems to be moving higher, but aren't ready to credit AI as opposed to more mundane efficiencies achieved during pandemic-era labor shortages. Even if the "baton" of productivity is now being passed, policymakers seem to be leaning toward a view that AI will cause structurally higher unemployment, not easily offset by lowering rates without risking higher inflation. Underpinning the Fed's framework is a long-run "natural" unemployment rate, currently thought to be around 4.2%, below which inflation pressures build. "If AI continues to raise productivity, economic growth could remain strong, even as churn in the labor market leads to an increase in unemployment. In a productivity boom such as this, a rise in unemployment may not indicate increased slack. As such, our normal demand-side monetary policy may not be able to ameliorate an AI-caused unemployment spell without also increasing inflationary pressure," Fed Governor Lisa Cook said last month, remarks echoed by several colleagues. The issue is hardly settled. Evercore ISI Vice Chair Krishna Guha sees a loss of worker bargaining power as a reason why the natural unemployment rate will fall as employees become willing to stay in jobs and accept lower wage increases, putting downward pressure on inflation - an argument that reaches conclusions similar to those of Warsh in terms of cutting interest rates but for somewhat different reasons. But the public comments from Fed officials have painted a more complex picture: jobs under pressure for some workers, new productive potential for others, wealth gains fueling consumption in some households, resource constraints during the AI buildout, and high expected investment returns likely to raise underlying interest rates. "There are lots of forecasts about both the rollout of AI, the effectiveness of AI, the energy efficiency of AI, the labor market implications of AI, and the only thing you know for sure is those forecasts are going to be wrong," Richmond Fed President Tom Barkin said last week. "Whether they are going to be too optimistic or too pessimistic you'll have to sort out as you go." (Reporting by Howard Schneider; Editing by Dan Burns and Andrea Ricci )