IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2509.15885.html

The Impact of AI Adoption on Retail Across Countries and Industries

Author

Listed:
  • Yunqi Liu

Abstract

This study investigates the impact of artificial intelligence (AI) adoption on job loss rates using the Global AI Content Impact Dataset (2020--2025). The panel comprises 200 industry-country-year observations across Australia, China, France, Japan, and the United Kingdom in ten industries. A three-stage ordinary least squares (OLS) framework is applied. First, a full-sample regression finds no significant linear association between AI adoption rate and job loss rate ($\beta \approx -0.0026$, $p = 0.949$). Second, industry-specific regressions identify the marketing and retail sectors as closest to significance. Third, interaction-term models quantify marginal effects in those two sectors, revealing a significant retail interaction effect ($-0.138$, $p

Suggested Citation

  • Yunqi Liu, 2025. "The Impact of AI Adoption on Retail Across Countries and Industries," Papers 2509.15885, arXiv.org.
    • Handle: RePEc:arx:papers:2509.15885
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2509.15885
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    2. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    3. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pablo Casas & Concepción Román, 2024. "The impact of artificial intelligence in the early retirement decision," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 583-618, August.
    2. Qianan Wang & Zen Chen, 2026. "Boom, Bubble, or Buildout? A Multi-Method Evaluation of Whether Artificial Intelligence Is in an Ongoing Financial Bubble," Papers 2606.01575, arXiv.org.
    3. Jetha, Arif & Liao, Qing & Shahidi, Faraz Vahid & Vu, Viet & Biswas, Aviroop & Smith, Brendan & Smith, Peter, 2025. "Machine learning and the labor market: A portrait of occupational and worker inequities in Canada," Social Science & Medicine, Elsevier, vol. 381(C).
    4. Xiang Hui & Oren Reshef & Luofeng Zhou, 2023. "The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market," CESifo Working Paper Series 10601, CESifo.
    5. Heluo, Yuxi & Fabel, Oliver, 2024. "Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    6. Andrea Gazzani & Filippo Natoli, 2026. "The macroeconomic effects of AI technology shocks," Temi di discussione (Economic working papers) 1542, Bank of Italy, Economic Research and International Relations Area.
    7. Paul E. Soto, 2025. "Research in Commotion: Measuring AI Research and Development through Conference Call Transcripts," Finance and Economics Discussion Series 2025-011, Board of Governors of the Federal Reserve System (U.S.).
    8. Matthias Oschinski & Christian Spielmann & Sonali Subbu-Rathinam, 2025. "AI and the future of work for economists: rethinking economics education," Bristol Economics Discussion Papers 25/788, School of Economics, University of Bristol, UK.
    9. Ekpeyong, Paul, 2025. "Artificial Intelligence, Task Automation and Macro-development: Modelling the productivity- welfare trade offs in the Nigeria Economy," MPRA Paper 125347, University Library of Munich, Germany.
    10. Estrada, Mario Arturo Ruiz & Park, Donghyun & Staniewski, Marcin, 2023. "Artificial Intelligence (AI) can change the way of doing policy modelling," Journal of Policy Modeling, Elsevier, vol. 45(6), pages 1099-1112.
    11. Mahmut Ozer & Matjaž Perc, 2020. "Dreams and realities of school tracking and vocational education," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 6(1), pages 1-7, December.
    12. David Rezza Baqaee & Emmanuel Farhi, 2018. "Macroeconomics with Heterogeneous Agents and Input-Output Networks," NBER Working Papers 24684, National Bureau of Economic Research, Inc.
    13. Anna-Maria Kanzola, 2024. "The Knowledge Content of the Greek Production Structure in the Aftermath of the Greek Crisis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 936-957, March.
    14. repec:eur:ejesjr:364 is not listed on IDEAS
    15. Benedetta Montanaro & Annalisa Croce & Elisa Ughetto, 2024. "Venture capital investments in artificial intelligence," Journal of Evolutionary Economics, Springer, vol. 34(1), pages 1-28, January.
    16. Xiangyi Li & Qing Wang & Ying Tang, 2024. "The Impact of Artificial Intelligence Development on Urban Energy Efficiency—Based on the Perspective of Smart City Policy," Sustainability, MDPI, vol. 16(8), pages 1-22, April.
    17. Zilian, Laura S. & Zilian, Stella S. & Jäger, Georg, 2021. "Labour market polarisation revisited: evidence from Austrian vacancy data," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-007.
    18. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    19. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    20. Chen Wu & Yang Cao & Hao Xu, 2025. "How Population Aging Drives Labor Productivity: Evidence from China," Sustainability, MDPI, vol. 17(11), pages 1-28, May.
    21. Gilbert Cette & Lorraine Koehl & Thomas Philippon, 2019. "The Labor Share in the Long Term: A Decline?," Post-Print hal-02446713, HAL.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2509.15885. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.