Regulatory models of artificial intelligence in contemporary governance: Comparative analysis of China, the EU and the USA

Download article
Article

Regulatory models of artificial intelligence in contemporary governance: Comparative analysis of China, the EU and the USA

Mykhailo Shkilniak

Received 04.07.2025, Revised 13.11.2025, Accepted 15.12.2025

https://doi.org/10.67524/verus1/1.2025.56

Retrieved from Vol. 1, No. 1, 2025

Pages 56-68

Abstract

The rapid development of artificial intelligence and its penetration into critically important spheres of social life have confronted global governance with unprecedented challenges that require the development of balanced regulatory approaches. The aim of this study was to compare the main regulatory models of artificial intelligence governance in the world’s leading regions – China, the European Union and the United States of America – and to identify areas of divergence as well as potential opportunities for mutual influence and adaptation within the contemporary political and ethical context. The research methodology was based on a combination of comparative, analytical and case-study methods. The regulatory frameworks and policies of the EU, the USA and China were analysed, along with case studies from Estonia, the African Union and leading technology corporations, which made it possible to identify differences in approaches to the regulation and practical application of artificial intelligence. The results of the study demonstrated that artificial intelligence has become a strategic resource shaping a new configuration of global power balances. The European regulatory model ensured a comprehensive approach to risk assessment through a multi-level classification of systems. The Chinese model demonstrated the effectiveness of centralised control and rapid scaling, while the American approach retained a fragmented character due to the absence of a single federal law. A trend was identified whereby international organisations play a role in shaping universal ethical standards, yet their capacity to ensure real coordination remains limited. It was found that the European Union’s “Brussels effect” contributes to the transnationalisation of European norms, while China and the United States disseminate their own models through digital diplomacy and corporate expansion respectively. Certain countries, such as Estonia, have demonstrated a successful combination of digitalisation of public administration with democratic principles, using cryptographic protection mechanisms and decentralised access to data. The results of the study may serve as a basis for developing adaptive strategies for artificial intelligence governance in countries with different levels of institutional development and may contribute to the formulation of international agreements in the field of digital policy

References
  1. Adrian, T., Ferati, E., Gates, I., Liu, L., Mendoza, K., Potnis, S., Schenk, Z., Srinivas, A., & Zachary, T. (2021). Misinformation in global media: Causes, consequences, and accountability. Seattle: Henry M. Jackson School of International Studies University of Washington
  2. African Union. (2024). Continental artificial intelligence strategy: Harnessing AI for Africa’s development and prosperity. Addis Ababa: African Union.
  3. AI Risk Management Framework. (2023). Retrieved from https://www.nist.gov/itl/ai-risk-management-framework.
  4. Akıner, N. (2024). A theoretical approach to the digital colonialism in the context of media imperialism. In 7th International conference on social science research (pp. 131-141). Durres: ICONSR.
  5. Allen, G.C. (2019). Understanding China's AI strategy: Clues to Chinese strategic thinking on artificial intelligence and national security.
  6. Anderson, M., Faverio, M., & Gottfried, J. (2023). Teens, social media and technology 2023: YouTube, TikTok, Snapchat and Instagram remain the most widely used online platforms among U.S. teens. Retrieved from https://www.pewresearch.org/internet/2023/12/11/teens-social-media-and-technology-2023/.
  7. Anshari, M., Hamdan, M., Ahmad, N., & Ali, E. (2025). Public service delivery, artificial intelligence and the sustainable development goals: Trends, evidence and complexities. Journal of Science and Technology Policy Management, 16(1), 163-181. doi: 10.1108/JSTPM-07-2023-0123.
  8. Antoliš, K. (2024). Disinformation supported by artificial intelligence from dynamic research to holistic solutions. Public Security and Public Order, 35, 11-23. doi: 10.13165/PSPO-24-35-02.
  9. Arslan, R., Özseven, T., & Aydın, M.M. (2025). Transforming European cybersecurity: AI-powered threat analysis, quantum age, blockchain/crypto risks, and regulatory strategies. International Journal of Engineering and Applied Sciences, 17(2), 81-93. doi: 10.24107/ijeas.1619600.
  10. Bajracharya, K. (2024). Big data and artificial intelligence integration in modernizing governance and public administration practices. Global Research Perspectives on Cybersecurity Governance, Policy, and Management, 8(12), 34-47.
  11. Basu, M., & Nath, M.D. (2024). A study of the role of artificial intelligence in monitoring environmental and health issues in the post-COVID-19 pandemic era for sustainable living. In X. Savarimuthu, S. Subramani & A.N.J. Raj (Eds.), Artificial intelligence for multimedia information processing: Tools and applications (pp. 132-166). Boca Raton: CRC Press.
  12. Blueprint for an AI Bill of Rights. (2022). The White House. Retrieved from https://bidenwhitehouse.archives.gov/ostp/ai-bill-of-rights/.
  13. Bornu, T.Z. (2025). The challenge of artificial intelligence in the middle east conflicts. The American Journal of Political Science Law and Criminology, 7(05), 115-129. doi: 10.37547/tajpslc/Volume07Issue05-14.
  14. Bradford, A. (2020). The Brussels effect: How the European Union rules the world. Oxford: Oxford University Press.
  15. Breuer, A. (2025). From polarisation to autocratisation: The role of information pollution in Brazil's democratic erosion. Bonn: German Institute of Development and Sustainability (IDOS). doi: 10.23661/idp2.2025.
  16. Caprotti, F., & Liu, D. (2022). Platform urbanism and the Chinese smart city: The co-production and territorialisation of Hangzhou City Brain. GeoJournal, 87(3), 1559-1573. doi: 10.1007/s10708-020-10320-2.
  17. Chen, T., Gascó-Hernandez, M., & Esteve, M. (2024). The adoption and implementation of artificial intelligence chatbots in public organizations: Evidence from US state governments. The American Review of Public Administration, 54(3), 255-270. doi: 10.1177/02750740231200522.
  18. Costa, S. (2023). Artificial intelligence: Ethical and political challenges. Santos Costa.
  19. Dixon, R.B.L. (2022). Artificial intelligence governance: A comparative analysis of China, the European Union, and the United States. (Professional paper, University of Minnesota Twin Cities, Minneapolis, MN).
  20. Dixon, R.B.L. (2023). A principled governance for emerging AI regimes: Lessons from China, the European Union, and the United States. AI and Ethics, 3, 793-810. doi: 10.1007/s43681-022-00205-0.
  21. Duygu, U. (2023). Between politics and social media: Examining domestic information operations through the Twitter controversy in Türkiye. (Master’s thesis, Sabancı University, Istanbul, Türkiye).
  22. Erman, E., & Furendal, M. (2024). Artificial intelligence and the political legitimacy of global governance. Political Studies, 72(2), 421-441. doi: 10.1177/00323217221126665.
  23. Erman, E., & Furendal, M. (2025). The democratic role of non-state actors in the global governance of artificial intelligence. Critical Review of International Social and Political Philosophy, 1-26. doi: 10.1080/13698230.2025.2520037.
  24. Espinosa, V.I., & Pino, A. (2025). E-Government as a development strategy: The case of Estonia. International Journal of Public Administration, 48(2), 86-99. doi: 10.1080/01900692.2024.2316128. 
  25. Filgueiras, F. (2022). Artificial intelligence policy regimes: Comparing politics and policy to national strategies for artificial intelligence. Global Perspectives, 3(1), article number 32362. doi: 10.1525/gp.2022.32362.
  26. Flew, T., & Hartig, F. (2014). Confucius institutes and the network communication approach to public diplomacy. The IAFOR Journal of Asian Studies, 1(1), 1-18.
  27. Fulbright (n.d.). Retrieved from https://fulbright.org.ua/uk/.
  28. Google. (n.d.). Retrieved from https://www.google.com/?hl=uk.
  29. Horizon Europe. (n.d.). Retrieved from https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe_en.
  30. Hu, Y., Kuang, W., Qin, Z., Li, K., Zhang, J., Gao, Y., Li, W., & Li, K. (2021). Artificial intelligence security: Threats and countermeasures. ACM Computing Surveys, 55(1), 1-36. doi: 10.1145/3487890.
  31. Kaun, A., & Männiste, M. (2025). Public sector chatbots: AI frictions and data infrastructures at the interface of the digital welfare state. New Media & Society, 27(4), 1962-1985. doi: 10.1177/14614448251314394.
  32. Kazemi, A., Garimella, K., Shahi, G.K., Gaffney, D., & Hale, S.A. (2022). Research note: Tiplines to uncover misinformation on encrypted platforms: A case study of the 2019 Indian general election on WhatsApp. Retrieved from https://misinforeview.hks.harvard.edu/article/research-note-tiplines-to-uncover-misinformation-on-encrypted-platforms-a-case-study-of-the-2019-indian-general-election-on-whatsapp/.
  33. Lillemets, P. (2023). Estonia – a digital government in digital transformation. (Master’s thesis, Tallinn University of Technology, Tallinn, Estonia).
  34. Lin, X. (2025). A model of big data-based governance: China’s national government big data platform and an analysis of its governance competence. Chinese Political Science Review, 10, 289-328. doi: 10.1007/s41111-025-00279-1.
  35. Maréchal, N., Renieris, E., Rydzak, J., Hartmann, I.A., Obar, J.A., Gaur, A., Macpherson, L., Karanicolas, M., & Keton, A. (2021). Tackling the ‘fake’ without harming the ‘news’: A paper series on regulatory responses to misinformation. Wikimedia/Yale Law School Initiative on Intermediaries and Information.
  36. Microsoft Dynamics 365. (n.d.). Retrieved from https://www.microsoft.com/uk-ua/microsoft-365.
  37. Mokry, S., & Gurol, J. (2024). Competing ambitions regarding the global governance of artificial intelligence: China, the US, and the EU. Global Policy, 15(5), 955-968. doi: 10.1111/1758-5899.13444.
  38. Netflix. (n.d.). Retrieved from https://www.netflix.com/tr-en/.
  39. Neupane, B. (2024). Artificial intelligence and big data technologies to optimize government decision-making processes in cloud-based environments. Journal of Artificial Intelligence and Machine Learning in Cloud Computing Systems, 8(11), 1-12.
  40. Neuwirth, R.J. (2024). The global institutional governance of AI: A four-dimensional perspective. International Journal of Digital Law and Governance, 1(1), 113-153. doi: 10.1515/ijdlg-2024-0004.  
  41. New e-Estonia factsheet: National AI “Kratt” strategy. (2020). Retrieved from https://e-estonia.com/new-e-estonia-factsheet-national-ai-kratt-strategy/.
  42. NVIDIA. (n.d.). Retrieved from https://www.nvidia.com/en-us/drivers/.
  43. Nwokike, L.I. (2022). The rising profile of international non-governmental organizations and their roles in contemporary concept of international governance. International Journal of Law and Clinical Legal Education, 3, 161-171.
  44. Nye, J.S. (2004). Soft power. Foreign Policy, 80, 153-171. doi: 10.2307/1148580.
  45. OpenAI. (n.d.). Retrieved from https://openai.com/.
  46. Parisini, E. (2025). Governing artificial intelligence in the defence sector: A comparative analysis of EU and US institutions. Global Public Policy and Governance, 5, 114-138. doi: 10.1007/s43508-025-00115-x.
  47. Radu, R. (2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy and Society, 40(2), 178-193. doi: 10.1080/14494035.2021.1929728.
  48. Recommendation on the Ethics of Artificial Intelligence. (2023). UNESCO. Retrieved from https://www.unesco.org/en/articles/recommendation-ethics-artificial-intelligence.
  49. Rincón, O., & Uribe-Rincón, C. (2024). Political communication in Latin America. In A. Casero-Ripollés & P.C. López-López (Eds.), The Routledge handbook of political communication in Ibero-America (pp. 19-31). London: Routledge. doi: 10.4324/9781003388937.
  50. Roberts, H., Cowls, J., Hine, E., Morley, J., Wang, V., Taddeo, M., & Floridi, L. (2023). Governing artificial intelligence in China and the European Union: Comparing aims and promoting ethical outcomes. The Information Society, 39(2), 79-97. doi: 10.1080/01972243.2022.2124565.
  51. State Council of the People’s Republic of China Document No. 35 “A New Generation of Artificial Intelligence Development Plan”. (2017, July). Retrieved from http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
  52. Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, 40(2), 137-157. doi: 10.1080/14494035.2021.1928377.
  53. The EU Artificial Intelligence Act. (2021). Retrieved from https://artificialintelligenceact.eu/.
  54. The Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules. (2021). Retrieved from https://www.meity.gov.in/static/uploads/2024/02/Information-Technology-Intermediary-Guidelines-and-Digital-Media-Ethics-Code-Rules-2021-updated-06.04.2023-.pdf#page=1.24.
  55. TikTok. (n.d.). Retrieved from https://www.tiktok.com/uk-UA/.
  56. Ulnicane, I., Knight, W., Leach, T., Stahl, B.C., & Wanjiku, W.G. (2022). Governance of artificial intelligence: Emerging international trends and policy frames. In M. Tinnirello (Ed.), The global politics of artificial intelligence (pp. 29-55). Boca Raton: CRC Press. doi: 10.1201/9780429446726-2.
  57. X-road – interoperability services. (n.d.). Retrieved from https://e-estonia.com/solutions/interoperability-services/x-road/.
  58. Zeng, J. (2020). Artificial intelligence and China’s authoritarian governance. International Affairs, 96(6), 1441-1459. doi: 10.1093/ia/iiaa172.  
  59. Zeng, J. (2022). Artificial intelligence with Chinese characteristics: National strategy, security and authoritarian governance. Singapore: Palgrave Macmillan Singapore. doi: 10.1007/978-981-19-0722-7.
Suggested citation
Shkilniak, M. (2025). Regulatory models of artificial intelligence in contemporary governance: Comparative analysis of China, the EU and the USA. Journal of Global Political Transformations, 1(1), 56-68. https://doi.org/10.67524/verus1/1.2025.56