The proliferation of artificial intelligence (AI) systems offers significant benefits but also presents considerable global risks. Despite the international nature of these risks, an internationally accepted governance framework for AI remains absent. This is largely due to geopolitical tensions and the lack of consensus among major global powers on the appropriate scope and methods for regulating AI development. The European Union (EU), China, and the United States are key players in AI regulation, each with divergent approaches. However, common themes can be identified to form the foundation of a global regulatory framework aimed at both managing risks and fostering innovation. This dissertation conducts a comparative analysis of AI regulations in the EU and China and examines the implications for the development of a global AI governance framework. Using deductive thematic analyses, the study explores the convergences and divergences in their regulatory approaches. While differences arise from China’s emphasis on socialist values, national security, minimal focus on individual rights, and geopolitical rivalry with the United States, there are areas of alignment. These include the categorisation of AI systems, safety measures, human-centric design, transparency, professional responsibility, privacy, and accountability. The study concludes that these shared regulatory principles could serve as a foundation for the development of a multilevel global AI framework. Such a framework should incorporate international, national, and industry-level governance with clearly defined outcomes and responsibilities. The United Nations, as a politically legitimate global forum with broad influence, including among China, is well-positioned to lead this effort.

The proliferation of artificial intelligence (AI) systems offers significant benefits but also presents considerable global risks. Despite the international nature of these risks, an internationally accepted governance framework for AI remains absent. This is largely due to geopolitical tensions and the lack of consensus among major global powers on the appropriate scope and methods for regulating AI development. The European Union (EU), China, and the United States are key players in AI regulation, each with divergent approaches. However, common themes can be identified to form the foundation of a global regulatory framework aimed at both managing risks and fostering innovation. This dissertation conducts a comparative analysis of AI regulations in the EU and China and examines the implications for the development of a global AI governance framework. Using deductive thematic analyses, the study explores the convergences and divergences in their regulatory approaches. While differences arise from China’s emphasis on socialist values, national security, minimal focus on individual rights, and geopolitical rivalry with the United States, there are areas of alignment. These include the categorisation of AI systems, safety measures, human-centric design, transparency, professional responsibility, privacy, and accountability. The study concludes that these shared regulatory principles could serve as a foundation for the development of a multilevel global AI framework. Such a framework should incorporate international, national, and industry-level governance with clearly defined outcomes and responsibilities. The United Nations, as a politically legitimate global forum with broad influence, including among China, is well�positioned to lead this effort.