ARTIFICIAL INTELLIGENCE AND GLOBAL ECONOMIC GOVERNANCE: THE NEED FOR AN INCLUSIVE INTERNATIONAL REGULATORY FRAMEWORK
DOI:
https://doi.org/10.29121/ShodhSamajik.v3.i3.2026.217Keywords:
Artificial Intelligence, Global Economic Governance, AI Regulation, Digital Divide, Inclusive Growth and International CooperationAbstract
Artificial Intelligence (AI) is revolutionizing production, trade, finance and work. It has inconsistent gains. The capital, compute and talent resides in a handful of countries and companies. Few are writing the rules. This paper raises the question whether the existing governance system can achieve equitable growth driven by AI. The design of the research is descriptive and secondary data. For the time frame 2019–2025, it refers to the periods 2020–2024 and 2021–2025, respectively, from the IMF, UNCTAD, OECD, ITU, Stanford AI Index and UN bodies. A melding of comparative tabulation and thematic policy analysis. Three findings emerge. It's global exposure to AI that's the first thing. Almost 40 per cent of employment is vulnerable worldwide, particularly in advanced economies. Secondly, capacity is centralised. In 2024, approximately US$109 billion was invested in AI by U.S. private companies, while approximately US$9 billion was invested in China, the largest market for AI outside the United States. Thirdly, there are multiple duly elected governance bodies. In a review done by the UN, 118 countries were identified as not having been involved in any of the seven large-scale initiatives on AI governance identified. Four gaps in participation, capacity, law and economic benefit are revealed from these findings. It suggests a four pillar approach to address them. It is based on minimum standards shared, a capacity and compute fund, mutual recognition of assessment and a representative oversight body. The paper then goes on to argue the importance of inclusion as a fairness question. Shared rules lower compliance costs, lessen the regulatory arbitrage, and expand the market for trusted AI. The framework is of a conceptual nature and requires empirical testing.
References
ASEAN. (2024). ASEAN Guide on AI Governance and Ethics. ASEAN Secretariat.
Abbott, K. W., and Snidal, D. (2000). Hard and Soft Law in International Governance. International Organization, 54(3), 421–456. https://doi.org/10.1162/002081800551280 DOI: https://doi.org/10.1162/002081800551280
Acemoglu, D., and Johnson, S. (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. PublicAffairs.
Acemoglu, D., and Restrepo, P. (2019). Automation and New Tasks: How Technology Displaces and Reinstates Labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3 DOI: https://doi.org/10.1257/jep.33.2.3
African Union. (2024). Continental Artificial Intelligence Strategy.
Ahmed, N., and Wahed, M. (2020). The De-Democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research [Preprint]. arXiv. https://arxiv.org/abs/2010.15581
Ahmed, N., Wahed, M., and Thompson, N. C. (2023). The Growing Influence of Industry in AI Research. Science, 379(6635), 884–886. https://doi.org/10.1126/science.ade2420 DOI: https://doi.org/10.1126/science.ade2420
Bowen, G. A. (2009). Document Analysis as a Qualitative Research Method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027 DOI: https://doi.org/10.3316/QRJ0902027
Bradford, A. (2020). The Brussels Effect: How the European Union rules the world. Oxford University Press. https://doi.org/10.1093/oso/9780190088583.001.0001 DOI: https://doi.org/10.1093/oso/9780190088583.001.0001
Braun, V., and Clarke, V. (2006). Using Thematic Analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa DOI: https://doi.org/10.1191/1478088706qp063oa
Bresnahan, T. F., and Trajtenberg, M. (1995). General Purpose Technologies: “Engines of Growth”? Journal of Econometrics, 65(1), 83–108. https://doi.org/10.1016/0304-4076(94)01598-T DOI: https://doi.org/10.1016/0304-4076(94)01598-T
Brynjolfsson, E., and McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton.
Brynjolfsson, E., Rock, D., and Syverson, C. (2021). The Productivity J-Curve: How Intangibles Complement General Purpose Technologies. American Economic Journal: Macroeconomics, 13(1), 333–372. https://doi.org/10.1257/mac.20180386 DOI: https://doi.org/10.1257/mac.20180386
Cazzaniga, M., Jaumotte, F., Li, L., Melina, G., Panton, A. J., Pizzinelli, C., Rockall, E., and Tavares, M. M. (2024). Gen-AI: Artificial Intelligence and the Future of Work (IMF Staff Discussion Note No. SDN/2024/001). International Monetary Fund. https://doi.org/10.5089/9798400262548.006 DOI: https://doi.org/10.5089/9798400262548.006
Cihon, P., Maas, M. M., and Kemp, L. (2020). Fragmentation and the Future: Investigating Architectures for International AI Governance. Global Policy, 11(5), 545–556. https://doi.org/10.1111/1758-5899.12890 DOI: https://doi.org/10.1111/1758-5899.12890
Couldry, N., and Mejias, U. A. (2019). The Costs of Connection: How Data is Colonizing Human Life and Appropriating it for Capitalism. Stanford University Press. https://doi.org/10.1515/9781503609754 DOI: https://doi.org/10.1515/9781503609754
Council of Europe. (2024). Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225).
David, P. A. (1990). The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox. American Economic Review, 80(2), 355–361.
European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act). Official Journal of the European Union.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., and Vayena, E. (2018). AI4People: An Ethical Framework for a Good AI Society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 DOI: https://doi.org/10.1007/s11023-018-9482-5
G20. (2019). G20 AI Principles [Annex to the Osaka Leaders' Declaration].
G7. (2023). Hiroshima Process International Guiding Principles and Code of Conduct for Organizations Developing Advanced AI Systems.
Hargittai, E. (2002). Second-Level Digital Divide: Differences in People's Online Skills. First Monday, 7(4). https://doi.org/10.5210/fm.v7i4.942 DOI: https://doi.org/10.5210/fm.v7i4.942
Hu, K. (2023, February 2). ChatGPT Sets Record for Fastest-Growing User Base, Analyst Note Says. Reuters.
International Monetary Fund. (2024). World Economic Outlook: Country Groups and Classification.
International Organization for Standardization. (2023). Information Technology—Artificial Intelligence—Management System (ISO/IEC Standard No. 42001:2023).
International Telecommunication Union. (2024). Facts and Figures 2024.
Jobin, A., Ienca, M., and Vayena, E. (2019). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2 DOI: https://doi.org/10.1038/s42256-019-0088-2
Johnston, M. P. (2014). Secondary Data Analysis: A Method of Which the Time has Come. Qualitative and Quantitative Methods in Libraries, 3(3), 619–626.
Korinek, A., and Stiglitz, J. E. (2017). Artificial Intelligence and Its Implications for Income Distribution and Unemployment (NBER Working Paper No. 24174). National Bureau of Economic Research. https://doi.org/10.3386/w24174 DOI: https://doi.org/10.3386/w24174
Lehdonvirta, V., Wu, B., and Hawkins, Z. (2024). Compute North vs. Compute South: The Uneven Possibilities of Compute-Based AI Governance Around the Globe. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 7(1). https://doi.org/10.31235/osf.io/8yp7z DOI: https://doi.org/10.31235/osf.io/8yp7z
Maslej, N., Fattorini, L., Perrault, R., Gil, Y., Parli, V., Kariuki, N., Capstick, E., Reuel, A., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., Niebles, J. C., Shoham, Y., Wald, R., Walsh, T., Hamrah, A., Santarlasci, L., . . . Oak, S. (2025). The AI Index 2025 Annual Report. Stanford Institute for Human-Centered AI, Stanford University.
Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. D., and Gebru, T. (2019). Model Cards for Model Reporting. In Proceedings of the Conference on Fairness, Accountability, and Transparency ( 220–229). ACM. https://doi.org/10.1145/3287560.3287596 DOI: https://doi.org/10.1145/3287560.3287596
Norris, P. (2001). Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press. https://doi.org/10.1017/CBO9781139164887 DOI: https://doi.org/10.1017/CBO9781139164887
OECD. (2019). Recommendation of the Council on Artificial Intelligence (OECD/LEGAL/0449). OECD Publishing.
OECD. (2024). Recommendation of the Council on Artificial Intelligence (As Amended) (OECD/LEGAL/0449). OECD Publishing.
Ragin, C. C. (2014). The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. University of California Press. https://doi.org/10.1525/9780520957350 DOI: https://doi.org/10.1525/9780520957350
Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., and Barnes, P. (2020). Closing the AI Accountability Gap: Defining an end-to-end Framework for Internal Algorithmic Auditing. In Proceedings of the Conference on Fairness, Accountability, and Transparency ( 33–44). ACM. https://doi.org/10.1145/3351095.3372873 DOI: https://doi.org/10.1145/3351095.3372873
UK Government. (2023). The Bletchley Declaration by Countries Attending the AI Safety Summit, 1–2 November 2023.
UNCTAD. (2025). Technology and Innovation Report 2025: Inclusive AI for Development. United Nations Conference on Trade and Development.
United Nations General Assembly. (2024). Seizing the Opportunities of Safe, Secure and Trustworthy Artificial Intelligence Systems for Sustainable Development (A/RES/78/265).
United Nations General Assembly. (2025). Resolution Establishing the Independent International Scientific Panel on Artificial Intelligence and the Global Dialogue on AI Governance (A/RES/79/325).
United Nations High-Level Advisory Body on AI. (2024). Governing AI for Humanity: Final Report. United Nations.
United Nations. (2024). Global Digital Compact [Annex I to the Pact for the Future].
Veale, M., Matus, K., and Gorwa, R. (2023). AI and Global Governance: Modalities, Rationales, Tensions. Annual Review of Law and Social Science, 19, 255–275. https://doi.org/10.1146/annurev-lawsocsci-020223-040749 DOI: https://doi.org/10.1146/annurev-lawsocsci-020223-040749
Van Dijk, J. (2005). The Deepening Divide: Inequality in the Information Society. Sage. https://doi.org/10.4135/9781452229812 DOI: https://doi.org/10.4135/9781452229812
Zimik, A. S. S., and Barman, A. (2024). Next Dynamics in Designing Artificial Intelligence to Support Tourism Development. International Journal of Engineering Technologies and Management Research, 11(6), 44–57. https://doi.org/10.29121/ijetmr.v11.i6.2024.606 DOI: https://doi.org/10.29121/ijetmr.v11.i6.2024.1465
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