AI growth increases US output volatility by 2.8 percent
A Kansas City Fed working paper finds that artificial intelligence development is concentrated in volatile occupations and has increased US output volatility by 2.8 percent, roughly 3.5 times the impact of the 1990s IT boom.
Concentrated in cyclical churn
Research by Juan David Munoz Henao and Nicholas Sly demonstrates that artificial intelligence technologies concentrate in jobs with elevated labor market volatility.
Occupations most exposed to AI historically feature four key dynamics: greater employment fluctuations during business cycles, higher job-switching rates, faster job-finding speeds, and a lower likelihood of workers exiting the labor force after job loss.
Furthermore, the industrial sectors producing AI technologies show high historical productivity volatility.
The authors calculate that recent expansion in AI production raised aggregate US output volatility by 2.8 percent, a response roughly 3.5 times larger than that produced by the late 1990s information technology boom.
Amplified by labor supply elasticity
The study illustrates how technology-driven structural changes reshuffle macro activity and amplify broader business cycle fluctuations.
If the concentration of AI in highly variable occupations increases overall labor supply elasticity, the resulting macroeconomic volatility could expand even further.
This structural shift distinguishes the ongoing AI transition from previous technological waves.
By tying core production processes to inherently unstable labor segments, the ongoing digital transformation creates a persistent channel for heightened economic variability across future economic cycles.
A structural price for progress
The study convincingly refutes the assumption that AI adoption brings effortless macroeconomic stability.
By linking worker churn directly to output swings, the paper offers clear empirical grounding for macro modeling.
Central bankers must prepare for structural technology transitions to amplify future business cycle volatility.