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2.3. AI Governance in Action- Global Strategies and Models

AI Governance in Action: Global Strategies and Models

Artificial intelligence is no longer governed solely by technical standards or corporate codes. It is increasingly shaped by national legislation, political ideology, and geopolitical strategy. Around the world, countries are racing not just to regulate AI, but to define the institutional rules, enforcement mechanisms, and public expectations that will determine how power is distributed in a digital society.

Who gets to decide how AI systems behave?

Whose values are encoded into national policy?

What does it mean to regulate AI in the public interest when governments, corporations, and global standards bodies all compete for influence?

This is not merely a compliance challenge, it is a framework problem.

Whether motivated by democratic values, economic competitiveness, or national security, every country’s approach to AI governance reflects a unique constellation of legal traditions, risk tolerance, institutional structures, and cultural assumptions.

In this section, we examine four distinctive governance models:

The European Union, which emphasizes enforceable rights, high-risk regulation, and lifecycle accountability

The United States, which leans on voluntary frameworks and decentralized, sector-based oversight

China, which centralizes control under state ideology and uses AI as an instrument of national strategy

South Korea, which experiments with agile regulatory tracks while aligning with international standards

Each model is not only a regulatory system; it is a vision of what AI should serve, and who it should answer to.

By comparing these approaches, readers will better understand:

  • The trade-offs between centralized control and decentralized innovation

  • The tensions between rapid deployment and public accountability

  • The risks of regulatory fragmentation across borders

  • The future implications of competing governance philosophies on global AI norms

As AI systems increasingly determine access to services, rights, and resources, national governance models will shape not only domestic outcomes, but the global trajectory of AI policy. Understanding their foundations is essential to any serious discussion of trustworthy AI.