IDEAS home Printed from https://ideas.repec.org/p/bis/bisblt/121.html

Economic impact of AI in emerging market economies

Author

Listed:
  • Leonardo Gambacorta
  • Enisse Kharroubi
  • Aaron Mehrotra
  • Livia Pancotto

Abstract

The productivity and growth effects of artificial intelligence (AI) vary widely across countries, reflecting differences in sectoral composition and in the capacity to adopt and deploy AI. While advanced economies (AEs) are generally better positioned to reap the benefits of AI in the near term, substantial heterogeneity exists within emerging market economies (EMEs). AI preparedness – covering digital infrastructure, skills and institutional capacity – is a key determinant of overall gains, amplifying productivity effects where it is strong and constraining them where gaps persist, particularly in many EMEs. Closing AI preparedness gaps can support long-term convergence, as stronger infrastructure, human capital and institutions would enable EMEs to harness AI more effectively, help mitigate labour market risks through reskilling and retraining policies, and narrow growth differences with AEs.

Suggested Citation

  • Leonardo Gambacorta & Enisse Kharroubi & Aaron Mehrotra & Livia Pancotto, 2026. "Economic impact of AI in emerging market economies," BIS Bulletins 121, Bank for International Settlements.
  • Handle: RePEc:bis:bisblt:121
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/bisbull121.pdf
    File Function: Full PDF document
    Download Restriction: no

    File URL: https://www.bis.org/publ/bisbull121.htm
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daron Acemoglu, 2025. "The simple macroeconomics of AI," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 13-58.
    2. Nicholas Crafts, 2021. "Artificial intelligence as a general-purpose technology: an historical perspective," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 521-536.
    3. Leonardo Gambacorta & Han Qiu & Shuo Shan & Daniel M Rees, 2024. "Generative AI and labour productivity: a field experiment on coding," BIS Working Papers 1208, Bank for International Settlements.
    4. Iñaki Aldasoro & Sebastian Doerr & Daniel Rees, 2026. "Financing the AI boom: from cash flows to debt," BIS Bulletins 120, Bank for International Settlements.
    5. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    6. Leonardo Gambacorta & Enisse Kharroubi & Aaron Mehrotra & Tommaso Oliviero, 2025. "Artificial intelligence and growth in advanced and emerging economies: short-run impact," BIS Working Papers 1321, Bank for International Settlements.
    7. Francesco Filippucci & Peter Gal & Matthias Schief, 2024. "Miracle or Myth? Assessing the macroeconomic productivity gains from Artificial Intelligence," OECD Artificial Intelligence Papers 29, OECD Publishing.
    8. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    9. Mauro Cazzaniga & Ms. Florence Jaumotte & Longji Li & Mr. Giovanni Melina & Augustus J Panton & Carlo Pizzinelli & Emma J Rockall & Ms. Marina Mendes Tavares, 2024. "Gen-AI: Artificial Intelligence and the Future of Work," IMF Staff Discussion Notes 2024/001, International Monetary Fund.
    10. Francesco Filippucci & Peter Gal & Katharina Laengle & Matthias Schief & Muhammed A. Yildirim, 2026. "AI meets trade: Global linkages and the cross-country distribution of the gains from AI," OECD Artificial Intelligence Papers 57, OECD Publishing.
    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. Iñaki Aldasoro & Leonardo Gambacorta & Rozalia Pal & Debora Revoltella & Christoph Weiss & Marcin Wolski, 2026. "AI adoption, productivity and employment: evidence from European firms," BIS Working Papers 1325, Bank for International Settlements.
    2. Florian Misch & Ben Park & Carlo Pizzinelli & Galen Sher, 2026. "Artificial Intelligence and Productivity in Europe," CESifo Working Paper Series 12401, CESifo.
    3. Leonardo Gambacorta & Tullio Jappelli & Tommaso Oliviero, 2025. "Exploring household adoption and usage of generative AI: new evidence from Italy," BIS Working Papers 1298, Bank for International Settlements.
    4. Nickel, Christiane & Kilponen, Juha & Moral-Benito, Enrique & Koester, Gerrit & Ciccarelli, Matteo & Enders, Almira & Holton, Sarah & Landau, Bettina & Venditti, Fabrizio & Bobeica, Elena & Brand, Cla, 2025. "A strategic view on the economic and inflation environment in the euro area," Occasional Paper Series 371, European Central Bank.
    5. Georgios A. Tritsaris, 2025. "Occupational Tasks, Automation, and Economic Growth: A Modeling and Simulation Approach," Papers 2512.16261, arXiv.org, revised Dec 2025.
    6. Borowski, Jakub & Fidrmuc, Jarko & Jaworski, Krystian, 2025. "Artificial intelligence and inflation in the EU," Economics Letters, Elsevier, vol. 257(C).
    7. Jakub Growiec, 2025. "GNPJE Special Issue on Economic Impacts of Generative AI," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 1-5.
    8. Cheng, Qiang & Lin, Pengkai & Zhao, Yue, 2025. "Does generative AI facilitate investor Trading? Early evidence from ChatGPT outages," Journal of Accounting and Economics, Elsevier, vol. 80(2).
    9. Riccardo Zanardelli, 2025. "Navigating the safe harbor paradox in human-machine systems," Papers 2509.14057, arXiv.org, revised Jan 2026.
    10. Ali Ansari & Mark Esposito & Ava Fitoussy & Liu Zhang, 2026. "No Last Mile: A Theory of the Human Data Market," Papers 2603.00932, arXiv.org.
    11. Lukas Althoff & Hugo Reichardt, 2026. "Task-Specific Technical Change and Comparative Advantage," CESifo Working Paper Series 12403, CESifo.
    12. Carlo Drago & Alberto Costantiello & Marco Savorgnan & Angelo Leogrande, 2025. "Macroeconomic and Labor Market Drivers of AI Adoption in Europe: A Machine Learning and Panel Data Approach," Economies, MDPI, vol. 13(8), pages 1-62, August.
    13. Alexander Cuntz & Carsten Fink & Hansueli Stamm, 2024. "Artificial Intelligence and Intellectual Property : An Economic Perspective," WIPO Economic Research Working Papers 77, World Intellectual Property Organization - Economics and Statistics Division.
    14. Fasheng Xu & Xiaoyu Wang & Wei Chen & Karen Xie, 2025. "The Economics of AI Foundation Models: Openness, Competition, and Governance," Papers 2510.15200, arXiv.org.
    15. Yongheng Hu, 2025. "Heterogeneous Agents in the Data Economy," Papers 2509.09656, arXiv.org.
    16. Jakubik, Adam & Rotunno, Lorenzo & Saini, Alisha, 2025. "Foresee the unseen: Evaluating the impact of artificial intelligence on international trade," Journal of Policy Modeling, Elsevier, vol. 47(4), pages 842-861.
    17. Flavio Calvino & Luca Fontanelli, 2026. "Decoding AI: an early look at how French firms use AI," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 16(1), pages 51-93, March.
    18. Vesely, Stepan & Amaris, Gloria, 2025. "AI-driven income inequality and preferences for redistribution," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 642-648.
    19. Carlo Drago & Alberto Costantiello & Marco Savorgnan & Angelo Leogrande, 2025. "Driving AI Adoption in the EU: A Quantitative Analysis of Macroeconomic Influences," Working Papers hal-05102974, HAL.
    20. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Firm Productivity: Field Experiments in Online Retail," Papers 2510.12049, arXiv.org, revised Feb 2026.

    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:bis:bisblt:121. 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: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    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.