Federal Reserve Study: Programmer Job Growth Halved Since ChatGPT Launched, ~500K Jobs Missing

Fed economists Leland Crane and Paul Soto find US programmer job growth dropped roughly 50% after ChatGPT's Nov 2022 launch, with the gap widening from mid-2024. They estimate ~500,000 developer jobs that would otherwise have existed never materialized.

Fed ChatGPT programmer study cover — 500K missing jobs, growth halved
Illustration: BlockAI News · Source: Federal Reserve FEDS Notes, April 27 2026

A new Federal Reserve study by economists Leland D. Crane and Paul E. Soto finds US programmer employment growth fell roughly 50% after ChatGPT launched in November 2022, with the gap widening sharply from mid-2024 onward. The researchers estimate roughly 500,000 developer jobs that would otherwise have existed simply never materialized.

The Numbers

Pre-ChatGPT, programming-heavy occupations were growing at just under 5% a year — well above the broader US labor market. Post-launch, growth in the most concentrated programmer sectors (IT services, software development) essentially flatlined. The Crane-Soto paper, published as a Fed Notes piece, frames this as the first institutional confirmation of what tech workers have anecdotally reported for two years.

The Lag

The gap didn't open immediately. The employment shift only appears clearly from mid-2024 — about 18 months after ChatGPT's launch. The authors interpret this as a "trust delay": companies needed time to see LLM coding capability improve through GPT-4, GPT-4 Turbo, Claude 3, and Gemini 1.5 before betting headcount on it. Once trust formed, hiring slowdowns compounded with the broader 2024 tech downturn, making causality hard to fully isolate.

AI Adoption and Firms' Job-Posting Behavior — FEDS Notes
Federal Reserve research on AI adoption signals in firm-level US job postings.

Our Take

500,000 missing jobs is a big number, but two caveats matter. One, the Fed's methodology compares actual to counterfactual hiring growth — it does not say AI caused 500K layoffs, but rather that 500K hires never happened. Two, the same period saw record investment in AI infrastructure roles, ML engineering, and applied research — suggesting the impact is uneven across the developer stack rather than uniform extinction. Watch the 2026 H1 BLS data: if junior engineer postings stay flat while senior infrastructure roles keep expanding, the bifurcation thesis hardens.

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How we report: This article cites primary sources, regulatory filings, and on-chain data where available. BlockAI News uses AI tools to assist with research and first-draft generation; every article is reviewed and edited by a human editor before publication. Read our full How We Report page, Editorial Policy, AI Use Policy, and Corrections Policy.

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