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AI-Accelerated Occupational Decline and the Mobility Trap

Author

Listed:
  • Xi Song
  • Jennie E. Brand
  • Sukie Xiuqi Yang
  • Michael Lachanski

Abstract

Economic transformation challenges workers beyond job creation or loss by reshaping their ability to move across occupations. This paper examines whether AI-driven occupational restructuring, accelerated after 2018 by transformer-based technologies, creates a “mobility trap” for workers in declining, high-AI-exposed occupations. Using BLS administrative data and CPS worker transitions, we analyze who moves, where they move, and with what outcomes. We find that while these workers are more mobile, they are 5.2 times more likely to move into another declining occupation than a growing one. Nearly 70 percent experience downward or lateral mobility, suggesting that AI-driven restructuring entrenches disadvantage rather than enabling upward mobility.

Suggested Citation

  • Xi Song & Jennie E. Brand & Sukie Xiuqi Yang & Michael Lachanski, 2026. "AI-Accelerated Occupational Decline and the Mobility Trap," AEA Papers and Proceedings, American Economic Association, vol. 116, pages 246-250, May.
    • Handle: RePEc:aea:apandp:v:116:y:2026:p:246-250
    DOI: 10.1257/pandp.20261004
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    More about this item

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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