IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/11073.html
   My bibliography  Save this paper

Beyond the AI Divide : A Simple Approach to Identifying Global and Local Overperformers in AI Preparedness

Author

Listed:
  • Pierre Jean-Claude Mandon

Abstract

This paper examines global disparities in artificial intelligence preparedness, using the 2023 Artificial Intelligence Preparedness Index developed by the International Monetary Fund alongside the multidimensional Economic Complexity Index. The proposed methodology identifies both global and local overperformers by comparing actual artificial intelligence readiness scores to predictions based on economic complexity, offering a comprehensive assessment of national artificial intelligence capabilities. The findings highlight the varying significance of regulation and ethics frameworks, digital infrastructure, as well as human capital and labor market development in driving artificial intelligence overperformance across different income levels. Through case studies, including Singapore, Northern Europe, Malaysia, Kazakhstan, Ghana, Rwanda, and emerging demographic giants like China and India, the analysis illustrates how even resource-constrained nations can achieve substantial artificial intelligence advancements through strategic investments and coherent policies. The study underscores the need for offering actionable insights to foster peer learning and knowledge-sharing among countries. It concludes with recommendations for improving artificial intelligence preparedness metrics and calls for future research to incorporate cognitive and cultural dimensions into readiness frameworks.

Suggested Citation

  • Pierre Jean-Claude Mandon, 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.
  • Handle: RePEc:wbk:wbrwps:11073
    as

    Download full text from publisher

    File URL: https://documents.worldbank.org/curated/en/099517502242572646/pdf/IDU-5c1b47f8-89d8-4064-8b72-329105034043.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Philip Trammell & Anton Korinek, 2023. "Economic Growth under Transformative AI," NBER Working Papers 31815, National Bureau of Economic Research, Inc.
    2. Hunt, Jennifer & Cockburn, Iain & Bessen, James, 2024. "Is distance from innovation a barrier to the adoption of artificial intelligence," LSE Research Online Documents on Economics 126840, London School of Economics and Political Science, LSE Library.
    3. Jones, Garett, 2011. "National IQ and National Productivity: The Hive Mind Across Asia," Asian Development Review, Asian Development Bank, vol. 28(1), pages 51-71.
    4. Zeugner, Stefan & Feldkircher, Martin, 2015. "Bayesian Model Averaging Employing Fixed and Flexible Priors: The BMS Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i04).
    5. Madsen, Jakob B., 2016. "Barriers to Prosperity: Parasitic and Infectious Diseases, IQ, and Economic Development," World Development, Elsevier, vol. 78(C), pages 172-187.
    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. Madsen, Jakob B., 2016. "Barriers to Prosperity: Parasitic and Infectious Diseases, IQ, and Economic Development," World Development, Elsevier, vol. 78(C), pages 172-187.
    2. Xindong Xue & W. Robert Reed & Robbie C.M. van Aert, 2022. "Social Capital and Economic Growth: A Meta-Analysis," Working Papers in Economics 22/20, University of Canterbury, Department of Economics and Finance.
    3. Abe, Ryosuke & Kato, Hironori, 2017. "What led to the establishment of a rail-oriented city? Determinants of urban rail supply in Tokyo, Japan, 1950–2010," Transport Policy, Elsevier, vol. 58(C), pages 72-79.
    4. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    5. Salahodjaev, Raufhon & Yuldashev, Oybek, 2016. "Intelligence and greenhouse gas emissions: Introducing Intelligence Kuznets curve," MPRA Paper 68997, University Library of Munich, Germany.
    6. Anna Sokolova, 2023. "Marginal Propensity to Consume and Unemployment: a Meta-analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 813-846, December.
    7. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    8. Isaac Kalonda-Kanyama & Oasis Kodila-Tedika, 2012. "Quality of Institutions : Does Intelligence Matter?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201206, University of Kansas, Department of Economics, revised Apr 2012.
    9. Lv, Zhike, 2017. "Intelligence and corruption: An empirical investigation in a non-linear framework," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 69(C), pages 83-91.
    10. Janus, Jakub, 2021. "The COVID-19 shock and long-term interest rates in emerging market economies," Finance Research Letters, Elsevier, vol. 43(C).
    11. Beata K. Bierut & Piot Dybka, 2019. "Institutional determinants of export competitiveness among the EU countries: evidence from Bayesian model averaging," KAE Working Papers 2019-043, Warsaw School of Economics, Collegium of Economic Analysis.
    12. Pérez-Centeno, Víctor, 2017. ""It takes three to tango": Brain, cognition and entrepreneurial enhancement," Working Papers 02/17, Institut für Mittelstandsforschung (IfM) Bonn.
    13. Roman Horvath & Ali Elminejad & Tomas Havranek, 2020. "Publication and Identification Biases in Measuring the Intertemporal Substitution of Labor Supply," Working Papers IES 2020/32, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    14. Chen Ray-Bing & Chen Yi-Chi & Chu Chi-Hsiang & Lee Kuo-Jung, 2017. "On the determinants of the 2008 financial crisis: a Bayesian approach to the selection of groups and variables," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-17, December.
    15. Salahodjaev, Raufhon & Azam, Sardor, 2015. "IQ and the Weight of Nations," MPRA Paper 66144, University Library of Munich, Germany.
    16. Rajeev K. Goel & James W. Saunoris, 2020. "A Replication of “Sorting through Global Corruption Determinants: Institutions and Education Matter—Not Culture†(World Development 2018)," Public Finance Review, , vol. 48(4), pages 538-567, July.
    17. Joseph, Andreas & Osbat, Chiara, 2016. "How you export matters: the disassortative structure of international trade," Working Paper Series 1958, European Central Bank.
    18. Laville,Camille & Mandon,Pierre Jean-Claude, 2023. "Internal Conflicts and Shocks. A Narrative Meta-Analysis," Policy Research Working Paper Series 10315, The World Bank.
    19. Florian Morvillier, 2018. "On the impact of the launch of the euro on EMU macroeconomic vulnerability," EconomiX Working Papers 2018-51, University of Paris Nanterre, EconomiX.
    20. Tomas Havranek & Dominik Herman & Zuzana Irsova, 2018. "Does Daylight Saving Save Electricity? A Meta-Analysis," The Energy Journal, , vol. 39(2), pages 35-61, March.

    More about this item

    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:wbk:wbrwps:11073. 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: Roula I. Yazigi (email available below). General contact details of provider: https://edirc.repec.org/data/dvewbus.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.