Introduction

On April 27, 2026, the National Development and Reform Commission of China announced a decision to prohibit foreign investment in the Manus project, marking the first publicly halted foreign acquisition in the AI sector. This decision underscores the importance of national security reviews for companies involved in critical technologies.

Global Consensus on AI Governance

The control of key AI technologies and core data security is a common understanding among major global economies. Training large AI models requires vast amounts of data, prompting countries to impose requirements for data security and sovereignty compliance during data collection, processing, and usage.

The EU’s AI Act sets the strictest global standards for privacy, bias, and copyright concerning training data. However, in 2025, the EU passed the Digital Comprehensive Act, easing restrictions on model training data to enhance innovation in the EU’s AI industry.

In March 2026, the White House released the National AI Legislative Framework. This framework shifts the core philosophy from “safe, reliable, trustworthy” to “innovation-driven, winning the AI race,” advocating for deregulation to ensure US dominance in the global AI competition. This shift signifies a legislative move from merely seeking technological leadership to systematically constructing a comprehensive ecological dominance.

Dialogue with Experts

In a dialogue with Yao Xu, Secretary-General of the Global AI Innovation Governance Center and Associate Researcher at Fudan University, the differences in AI regulations and governance approaches among China, the US, and the EU were analyzed. Yao emphasized the risks of AI exacerbating global inequality and the digital divide.

US AI Legislative Framework: Domestic Consensus Lacking, Global Output Distant

Interviewer: A few years ago, the EU’s General Data Protection Regulation (GDPR) gained global recognition. Can the Trump administration’s National AI Legislative Framework establish a new consensus?

Yao Xu: Unlikely. The framework’s principles of “federal priority” and “preemption” challenge the traditional power distribution in the US federal system, leading to backlash from tech-forward states like California, which has already enacted advanced digital legislation. Moreover, the framework reflects strong partisan ideological biases, with the Republican push for deregulation seen as extreme by Democrats, who previously emphasized safety and trustworthiness.

The Impact of US-China Tech Competition

Interviewer: Does competition with China influence US AI regulation?

Yao Xu: Yes, the competitive pressure from China is significant, prompting the US to view AI as a strategic tool to maintain its global ecological dominance. Internally, the US faces various constraints, including the balance between federal and state powers, ideological struggles between parties, and conflicts between tech giants and small enterprises.

Global Divergence in AI Governance

Interviewer: Can the EU’s AI Act replicate the global influence of GDPR?

Yao Xu: GDPR is a crucial reference point, having established a framework for personal data protection globally. However, since its implementation, the EU has lagged in the digital economy and is now reassessing its regulatory approach. Other countries have adopted GDPR-like regulations, but the EU’s introspection has created a mismatch in timing, limiting its ability to adapt quickly.

Interviewer: How do you evaluate the regulatory paths of the EU, US, and China?

Yao Xu: While there are distinct regulatory characteristics, I oppose rigid categorizations. AI governance involves dynamic negotiations among various stakeholders, including national security, ethical standards, and corporate interests. The regulatory landscape is not static but evolves based on each country’s capabilities and interests.

Future Trends in AI Regulation

Interviewer: Will global AI regulatory trends converge or diverge?

Yao Xu: Currently, no country will outright reject AI development or impose excessive regulation. However, the strength of AI legal frameworks varies based on national capabilities and historical governance paths. The EU’s emphasis on strict regulations contrasts with the US’s more flexible approach, influenced by its rapid technological advancements.

Interviewer: What challenges will Chinese AI companies face when expanding internationally?

Yao Xu: Chinese firms will encounter significant challenges, particularly from the US’s comprehensive AI development strategy. The need for localization and compliance with diverse regulations will increase operational costs and complexity.

Conclusion: The Path Forward

Interviewer: What should be prioritized in China’s future AI regulations?

Yao Xu: China has developed several regulatory tools that effectively guide AI governance. Instead of a comprehensive legislative approach, it is essential to iterate and adapt existing regulations. The focus should be on addressing current policy constraints and enhancing international cooperation in AI development.

Yao Xu’s Concerns: The global South faces significant challenges in AI development due to a lack of infrastructure and skilled personnel. Addressing these disparities is crucial for equitable global AI governance.