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AI unbound: digital infrastructure, AI adoption, and firm performance

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  • Nuriye Melisa Bilgin
  • Gianmarco Ottaviano

Abstract

We study how digital infrastructure relaxes constraints on the diffusion and economic impact of artificial intelligence (AI). Using administrative data and a nationally representative enterprise survey from Turkey (2021-2024), we document significant disparities in AI adoption. Adoption is concentrated among large firms and in regions with high-speed broadband and proximity to data centers, particularly for software-intensive and cloud-based applications. To identify causal effects, we exploit the staggered expansion of Turkey's national natural gas pipeline network, which serves as a conduit for fiber-optic deployment. Because pipeline routing is determined by energy distribution priorities rather than digital demand, it provides plausibly exogenous variation in connectivity. Difference-in-differences estimates show that improved connectivity significantly increases AI adoption, particularly for software-intensive technologies and among small and medium-sized enterprises. Instrumental-variable estimates indicate that infrastructure-driven AI adoption raises labor productivity and export intensity while shifting labor composition toward ICT-related roles. These findings highlight digital infrastructure as a primary determinant of both the pace of AI diffusion and its resulting economic returns.

Suggested Citation

  • Nuriye Melisa Bilgin & Gianmarco Ottaviano, 2026. "AI unbound: digital infrastructure, AI adoption, and firm performance," CEP Discussion Papers dp2172, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp2172
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    References listed on IDEAS

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    1. Banu Demir & Beata Javorcik & Piyush Panigrahi, 2024. "Breaking Invisible Barriers: Does Fast Internet Improve Access to Input Markets?," Economics Series Working Papers 1061, University of Oxford, Department of Economics.
    2. Aldasoro, Iñaki & Gambacorta, Leonardo & Pal, Rozalia & Revoltella, Debora & Weiss, Christoph & Wolski, Marcin, 2026. "AI adoption, productivity and employment: Evidence from European firms," EIB Working Papers 2026/02, European Investment Bank (EIB).
    3. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
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    Cited by:

    1. Bilgin, Nuriye Melisa & Ottaviano, Gianmarco, 2026. "Skills, Not Scale: GenAI and Technology Adoption," CEPR Discussion Papers 21506, Centre for Economic Policy Research.

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    Keywords

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    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
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • 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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