Local Heterogeneity in Artificial Intelligence Jobs over Time and Space

Lefteris Andreadis, Eleni Kalotychou, Manolis Chatzikonstantinou, Christodoulos Louca and Christos A. Makridis

AEA Papers and Proceedings, 2025, vol. 115, 29-34

Abstract: We examine the spatial dynamics of AI adoption in the United States, leveraging county-level job postings data from 2014 to 2023. We document significant variation in AI intensity across counties and rapid growth occurring in unexpected suburban and remote-friendly areas such as Maries, Missouri, and Hughes, South Dakota. Controlling for county and year fixed effects, we find that higher shares of STEM degrees, labor market tightness, patent activity, lower manufacturing intensity, and turnover rates are key drivers of AI adoption. Our results point to the critical role of local education, innovation, and labor market dynamics in shaping adoption patterns.

JEL-codes: C45 I26 J23 J24 M15 O32 R23 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1257/pandp.20251001

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