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Journal Article
Downside Risk to the Stock Market and Consumption
Mitra, Indrajit; Rapach, David E. (2026-09-02)
We investigate downside risk to the stock market and, in turn, downside risk to consumption via the equity wealth effect. The AI boom has seen stock market valuations rise sharply, led by the so-called Magnificent 7, raising concerns of a stock market "bubble." We analyze potential factors contributing to downside risk to the stock market if investor sentiment turns decidedly more negative, thereby driving down equity prices. Downside risk to the stock market in turn poses downside risk to consumption spending via the equity wealth effect. We measure the equity wealth effect using data on ...
Policy Hub , Volume 2026 , Issue 6 , Pages 30

Journal Article
Downside Risk to the Stock Market and Consumption
Mitra, Indrajit; Rapach, David E. (2026-09-02)
We investigate downside risk to the stock market and, in turn, downside risk to consumption via the equity wealth effect. The AI boom has seen stock market valuations rise sharply, led by the so-called Magnificent 7, raising concerns of a stock market “bubble.” We analyze potential factors contributing to downside risk to the stock market if investor sentiment turns decidedly more negative, thereby driving down equity prices. Downside risk to the stock market in turn poses downside risk to consumption spending via the equity wealth effect. We measure the equity wealth effect using data on ...
Policy Hub , Volume 2026 , Issue 6 , Pages 30

Working Paper
Firm Data on AI
Meyer, Brent; Mizen, Paul; Bloom, Nicholas; Barrero, Jose Maria; Wang, Ben; Yotzov, Ivan; Thwaites, Gregory; Bunn, Philip; Navarrete, Michael; Jalca, Aaron; Davis, Steven J.; Smietanka, Pawel; Foster, Kevin (2026-03-24)
We present the first representative international data on firm-level AI use. We survey almost 6,000 CFOs, CEOs, and executives from stratified firm samples across the US, UK, Germany, and Australia. We find four key facts. First, around 70 percent of firms actively use AI, particularly younger, more productive firms. Second, while over two-thirds of top executives regularly use AI, their average use is only 1.5 hours a week, with one quarter reporting no AI use. Third, firms report little impact of AI over the last three years, with more than 80 percent of firms reporting no impact on either ...
FRB Atlanta Working Paper , Paper 2026-3

Working Paper
Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives
Meyer, Brent; Waddell, Sonya Ravindranath; Weitz, Daniel J.; Edwards, Zach; Baslandze, Salomé; McClure, Ty; Graham, John; Sparks, Michael (2026-03-25)
We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. These gains are not primarily driven by firms' capital deepening but instead reflect increases in ...
FRB Atlanta Working Paper , Paper 2026-04

Report
Shaping the Future of Work: Workers’ Optimism and Pessimism about AI
Bracha, Anat; Tang, Jenny (2025-12-17)
The artificial intelligence (AI) revolution is here and is expected to transform the labor market, creating new opportunities for some workers while eliminating the jobs of others. At the end of 2024, the authors of this brief surveyed a sample of US household heads working in different industries and with different educational backgrounds to better understand how they view AI and its potential effects on their job prospects and financial well-being.
Current Policy Perspectives , Paper 25-16

Working Paper
The Recent Evolution of AI-Related Labor Demand
Rinz, Kevin (2026-09-24)
AI mentions in US job advertisements have increased substantially since the beginning of 2024. The increase is concentrated in occupations more intensely exposed to the capabilities of large language models: one additional standard deviation of exposure is associated with a 3.1 percentage point increase in the rate at which job ads mention AI. Alongside this increase in AI mentions, more exposed occupations have seen job postings stabilize after a period of relative decline, posted wages rise, and hires and separations rise, all relative to less exposed occupations. Realized wages for new ...
Working Papers , Paper 26-24

Journal Article
New disruption from artificial intelligence exposes high-skilled workers
Su, Yichen; Pranger, Ana (2023-11-29)
With workers still grappling with the consequences of automation, the lightning-speed pace of artificial intelligence (AI) development poses fresh concerns of a new wave of worker displacement.
Southwest Economy

Working Paper
Processing Power: The Effect of Data Centers on Wholesale Electricity Markets
Kay, Owen; Taylor, Reid; Reaser, Robert (2026-10)
Data centers are reversing two decades of flat U.S. electricity demand. We estimate their effect on wholesale electricity markets using an hourly, unit-level dispatch model in which 23 U.S. regional markets trade over capacity-constrained interfaces. Data centers raised wholesale prices by 6.9 percent nationally by 2025 and by 15.0 percent in northern Virginia; under our preferred scenario, the national effect reaches 12.3 percent by 2028. Trade spreads these effects to regions hosting few data centers. Roughly half the increase in generator payments is a transfer to inframarginal generators. ...
Working Papers , Paper 2606

Working Paper
Processing Power: The Effect of Data Centers on Wholesale Electricity Markets
Kay, Owen; Taylor, Reid; Reaser, Robert (2026-03-20)
Artificial-intelligence-driven data centers are reversing two decades of flat U.S. electricity demand and have generated questions about how this growth will impact electricity prices. We quantify this effect using an hourly, unit-level least-cost dispatch model covering wholesale electricity markets in the continental United States. We find that existing data centers have already increased wholesale prices by 3 to 5% on average nationwide, with substantially larger effects in regions hosting major data center corridors. Extending the model through 2028, we show that if proposed construction ...
Working Papers , Paper 2606

Journal Article
On-the-Job Exposure to AI Among Lower-Income Workers
Kneebone, Elizabeth; Holmes, Natalie (2025-11-21)
To better understand the potential impacts of generative AI (gen AI) on the economy, this analysis uses quantitative methods to assess the extent to which workers are likely to be exposed to AI on the job, paying particular attention to workers in lower-income households, the occupations and industries in which they work, and how exposure varies across different parts of the country. It also draws on qualitative insights to understand how the impacts of AI integration are showing up in real time and how workforce and training organizations, nonprofits, and employers are adapting.
Community Development Research Brief , Volume 2025 , Issue 03 , Pages 27

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