Generative AI and the Reorganization of Labor Demand
The paper examines how generative AI is reshaping labor demand across various sectors. It highlights that firms are adjusting their hiring practices and redesigning job tasks in response to AI technology. The findings indicate that labor-market adjustments are a dynamic process involving both reallocation of demand and task reconfiguration.
- ▪Generative AI exposure is dynamic and changes significantly over time.
- ▪Hiring reallocation accounts for 52% of the aggregate decline in exposure, while within-job redesign contributes 39.5%.
- ▪Senior jobs adjust earlier through reallocation, whereas junior jobs adapt through a combination of reallocation and redesign.
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Economics > General Economics arXiv:2605.23159 (econ) [Submitted on 22 May 2026] Title:Generative AI and the Reorganization of Labor Demand Authors:Fangyan Wang, Zaiyan Wei, Yang Wang View a PDF of the paper titled Generative AI and the Reorganization of Labor Demand, by Fangyan Wang and 2 other authors View PDF Abstract:Generative artificial intelligence (AI) is expected to transform work, but less is known about how firms reorganize labor demand as the technology diffuses. Existing research has largely focused on which occupations are exposed to AI or whether exposed jobs decline. We extend this debate by examining whether firms adjust by changing where they hire, what jobs contain, or both.
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