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Discussion Paper
Automation and AI: What Does Adoption Look Like for Fifth District Businesses?
Corcoran, Emily Waverling; Waddell, Sonya Ravindranath (2024-06-27)
Technological developments shift the kinds of skills needed in the labor force. From innovations in agriculture to electricity to the personal computer to the internet, technology has shaped the way we work and the types of workers we need to produce the goods and provide the services that consumers demand. The tight labor market of the last few years has provided employers with further incentive to find ways to use automation to increase the productivity of existing workers and even reduce the need to hire more. The opportunities of artificial intelligence (AI), particularly generative AI, ...
Regional Matters

Working Paper
New Technologies and Jobs in Europe
Albanesi, Stefania; Jimeno, Juan F.; Lamo, Ana; Dias da Silva, António; Wabitsch, Alena (2024-11-18)
We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and software in 16 European countries over the period 2011-2019. Using data for occupations at the 3-digit level, we find that on average employment shares have increased in occupations more exposed to AI. This is particularly the case for occupations with a relatively higher proportion of younger and skilled workers. While there exists heterogeneity across countries, only very few countries show a decline in employment shares of occupations more exposed to AI-enabled automation. ...
Opportunity and Inclusive Growth Institute Working Papers , Paper 105

Journal Article
Features: Will AI Investments Pay Off?
Wells, Matthew (2026-04-15)
Artificial intelligence (AI) is having a moment. In its Real-Time Population Survey, the St. Louis Fed found that 55 percent of people in the United States reported using AI as of August 2025. Stanford University reported that businesses adopted AI at a 78 percent clip in 2024, up from 55 percent the year before. This adoption rate exceeds those of personal computers and the internet at comparable stages.In response to this interest, companies are spending billions on the equipment, research and development, and infrastructure required to accommodate the demand from businesses seeking to ...
Econ Focus , Volume 26 , Issue Q1/Q2 , Pages 10-13

Working Paper
Artificial Intelligence and Inflation Forecasts
Leibovici, Fernando; Faria-e-Castro, Miguel (2024-02-26)
We explore the ability of Large Language Models (LLMs) to produce in-sample conditional inflation forecasts during the 2019-2023 period. We use a leading LLM (Google AI's PaLM) to produce distributions of conditional forecasts at different horizons and compare these forecasts to those of a leading source, the Survey of Professional Forecasters (SPF). We find that LLM forecasts generate lower mean-squared errors overall in most years, and at almost all horizons. LLM forecasts exhibit slower reversion to the 2% inflation anchor.
Working Papers , Paper 2023-015

AI and Productivity Growth: Evidence from Historical Developments in Other Technologies
Kalyani, Aakash; Hogan, Marie (2024-04-04)
An analysis of the diffusion of PCs, smart devices, cloud computing and 3D printing suggests that AI may spread in a pattern similar to those of PCs and cloud computing.
On the Economy

Working Paper
Will AI Intensify or Weaken Market Competition?
Firooz, Hamid; Leduc, Sylvain; Liu, Zheng (2026-08-10)
We study how AI affects market competition based on a general equilibrium framework with heterogeneous firms facing idiosyncratic productivity and variable markups. Firms choose the AI technology subject to fixed costs, where AI production requires data and energy inputs. Our model predicts a non-monotonic relation of AI diffusion with industry concentration. As AI usage rises from an initially low level, large incumbent users gain market share. When AI usage is sufficiently diffused, entry of new and smaller adopters erodes the market share of incumbents, reducing industry concentration. The ...
Working Paper Series , Paper 2026-15

Working Paper
Research in Commotion: Measuring AI Research and Development through Conference Call Transcripts
Soto, Paul E. (2025-02-12)
This paper introduces a novel measure of firm-level Artificial Intelligence (AI) Research & Development—the AIR Index—derived from the semantic similarity between earnings conference call transcripts and leading AI research papers. The AIR Index varies widely across industries, with sustained strength in computer and electronic manufacturing, and accelerating growth in computing infrastructure and educational services seen after the introduction of ChatGPT in November 2022. I find that the AIR Index is associated with an immediate increase in Tobin’s Q and can help explain the ...
Finance and Economics Discussion Series , Paper 2025-011

Journal Article
Is Optimism for Artificial Intelligence Boosting Investment?
Li, Huiyu; Kalyani, Aakash (2026-05-18)
U.S. business spending related to artificial intelligence (AI) grew substantially in 2025 among publicly traded firms, which account for the bulk of overall investment. Analyzing sentiment data from quarterly company earnings calls can help infer current and evolving optimism towards AI. Public firm data show growth in capital spending and research and development funding has come entirely from the largest companies that are positive about AI. While market concentration among large firms raises some challenges, optimism measures suggest that AI investment will continue to contribute to future ...
FRBSF Economic Letter , Volume 2026 , Issue 13 , Pages 6

Working Paper
Forecasting the Economic Effects of AI
Karger, Ezra; Kuusela, Otto; Abaluck, Jason; Bryan, Kevin; Halperin, Basil; Jones, Todd; Murphy, Connacher; Trammell, Phil; Reynolds, Matt; Mayland, Dan; Viswanathan, Ria; Mittal, Ananaya; Ceppas de Castro, Rebecca; Rosenberg, Josh; Tetlock, Philip (2026-03)
We elicit forecasts of how AI will affect the U.S. economy, comparing the beliefs of five groups: academic economists, employees at AI companies, policy researchers focused on AI, highly accurate forecasters, and the general public. The median respondent in each group expects substantial advances in AI capabilities by 2030, small declines in labor force participation consistent with demographic shifts, and an annual GDP growth rate of 2.5%, which exceeds both the typical medium-run (2.0%) and long-run (1.7%) baseline forecasts from government agencies and private-sector forecasters. ...
Working Paper Series , Paper WP 2026-07

Journal Article
AI-Powered Algorithmic Pricing and Monetary Policy
Avaradi, Greeshma; Liu, Zheng; Zhao, Steven (2026-05-11)
The business practice of adjusting prices using algorithms powered by artificial intelligence—known as AI pricing—has grown rapidly and spread across many sectors in the economy. Unlike traditional price setting, AI pricing uses predictive analysis of large data sets to incorporate real-time changes in supply and demand conditions into pricing decisions. This enables businesses to adjust prices more quickly in response to unexpected changes in market conditions and monetary policy. Industry-level evidence suggests that price adjustments are more sensitive to monetary policy in sectors ...
FRBSF Economic Letter , Volume 2026 , Issue 12 , Pages 5

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