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Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence?

Author

Listed:
  • Jennifer Hunt
  • Iain M. Cockburn
  • James Bessen

Abstract

Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations.

Suggested Citation

  • Jennifer Hunt & Iain M. Cockburn & James Bessen, 2024. "Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence?," NBER Working Papers 33022, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:33022
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    Cited by:

    1. Wang, Yuxin & Zhou, Junting & Zhang, Rui, 2025. "Market accessibility, agglomeration, and spatial location of digital enterprises," International Review of Economics & Finance, Elsevier, vol. 98(C).
    2. Hamid Etemad, 2024. "Transformative potentials of generative artificial intelligence: Should international entrepreneurial enterprises adopt GEN.AI?," Journal of International Entrepreneurship, Springer, vol. 22(2), pages 141-163, June.
    3. Mandon, Pierre Jean-Claude, 2025. "Beyond the AI Divide : A Simple Approach to Identifying Global and Local Overperformers in AI Preparedness," Policy Research Working Paper Series 11073, The World Bank.
    4. Jeffery Piao & K. Philip Wang & Diana L. Weng, 2025. "U.S. Banks’ Artificial Intelligence and Small Business Lending: Evidence from the Census Bureau’s Annual Business Survey," Working Papers 25-07, Center for Economic Studies, U.S. Census Bureau.
    5. Kaicheng Zhang & Kai Liu & Caihong Huang, 2024. "Cooperative Innovation Under the “Belt and Road Initiative” for Reducing Carbon Emissions: An Estimation Based on the Spatial Difference-in-Differences Model," Sustainability, MDPI, vol. 16(23), pages 1-32, November.
    6. Liu, Yan & Huang, Jingyun & Wang, He, 2025. "Who on Earth Is Using Generative AI ? Global Trends and Shifts in 2025," Policy Research Working Paper Series 11231, The World Bank.
    7. Frank M. Fossen & Trevor McLemore & Alina Sorgner, 2024. "Artificial Intelligence and Entrepreneurship," Foundations and Trends(R) in Entrepreneurship, now publishers, vol. 20(8), pages 781-904, December.

    More about this item

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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