Local Heterogeneity in Artificial Intelligence Jobs over Time and Space
Lefteris Andreadis, Eleni Kalotychou, Manolis Chatzikonstantinou, Christodoulos Louca, Christos Andreas Makridis · AEA Papers and Proceedings · 1 May 2025
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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.
About this publication
Ranked journal. A peer-reviewed journal in the RePEc ranking of economics journals, below the leading ones.
Placed by: RePEc journal ranking. How sources are ranked.
- Published
- 2025 (18 months ago)
- Citations
- 6 (OpenAlex)
Citations in context
6 citations — 45th percentile among the 33 indexed papers from 2025 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature.
□ added to this collection in 2026.
Christos Makridis signed the wemustactnow.ai letter · author affiliation matches seed institutions arizona state university, georgetown university — part of why this paper is in the collection.
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