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On-the-Job Exposure to AI Among Lower-Income Workers

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Abstract

To better understand the potential impacts of generative AI (gen AI) on the economy, this analysis uses quantitative methods to assess the extent to which workers are likely to be exposed to AI on the job, paying particular attention to workers in lower-income households, the occupations and industries in which they work, and how exposure varies across different parts of the country. It also draws on qualitative insights to understand how the impacts of AI integration are showing up in real time and how workforce and training organizations, nonprofits, and employers are adapting.

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  • Natalie Holmes & Elizabeth Kneebone, 2025. "On-the-Job Exposure to AI Among Lower-Income Workers," Community Development Research Brief, Federal Reserve Bank of San Francisco, vol. 2025(03), pages 1-27, November.
    • Handle: RePEc:fip:fedfcb:102165
    DOI: 10.24148/cdrb2025-03
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    1. Sergio Galeano & Nye Hodge & Alexander Ruder, 2025. "By Degree(s): Measuring Employer Demand for AI Skills by Educational Requirements," Workforce Currents 2025-01, Federal Reserve Bank of Atlanta.
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