The Great Labor Displacement

This working paper estimates how much of the United States workforce could experience significant AI-related job disruption by 2030. It combines occupation-level AI-exposure measures with explicit assumptions about adoption, pass-through from exposure to substitution, and an adjustment for work that requires physical presence, and runs them across base and fast-adoption scenarios. In the base scenarios roughly 40 to 44 percent of U.S. jobs face significant disruption; in the fast scenarios the share exceeds 50 percent (about 52 to 54 percent). These are scenario estimates, not forecasts of job losses: disruption includes task restructuring, wage pressure and displacement. The model and its code are published in full so the assumptions can be checked. The physical-work adjustment currently uses an occupation-level proxy, and an independent methodological review by a labor economist is pending; both will be reflected in Version 3.2. Working paper, Version 3.1. Not peer-reviewed. The author develops AI businesses and has a commercial interest in the technology discussed. Drafting, analysis and code were produced with AI assistance under the author's direction; the author is responsible for all content. No external funding. Canonical page: https://www.oiail.org/publications/the-great-labor-displacement