China’s Approach to AI Regulation and How it Compares Globally

China has emerged as a global leader in artificial intelligence (“AI”), not only in terms of technological innovation but also in establishing a comprehensive regulatory framework. Since the launch of its Next Generation AI Development Plan (2017), the government has pursued a strategy of fostering innovation while exercising strict oversight to safeguard national security, social stability and ethical standards.

Recent regulatory milestones, from deep synthesis provisions to generative AI measures and mandatory AI education, reflect China’s determination to shape AI development in line with state priorities. This dual strategy of innovation and control has significant implications both domestically and internationally, as China’s model increasingly influences global debates on AI governance.

At the same time, these policies are increasingly setting benchmarks that reverberate beyond China’s borders, influencing how other major jurisdictions — the EU, UK and US — approach AI governance. This article examines China’s regulatory model, key milestones and its global implications, while drawing comparisons with other leading frameworks.

Strategic Vision for AI Development

China’s AI ambitions were formally articulated in the Next Generation Artificial Intelligence Development Plan, unveiled in 2017. This policy sets a target for China to become the world’s leading AI power by 2030, framing AI as integral to economic transformation and national security. The government seeks to embed AI as a fundamental driver of the country’s technological and economic future through long-term planning and centralised oversight.

Key Regulatory Milestones

China’s regulatory framework for AI has rapidly expanded since 2021, targeting both risks and opportunities in digital and data-driven technologies:

Deep Synthesis Provisions (2023)
Introduced on 10 January 2023, these rules regulate deep learning, virtual reality and other technologies used to generate synthetic content (including text, images, audio and video). The provisions apply across the entire content lifecycle — from creation to dissemination — and impose obligations on both providers and users. A central feature is mandatory labelling of deepfake content, aimed at curbing deception and misuse.
Interim Measures for Generative AI Services (2023)
In force since 15 August 2023, these measures apply to publicly available generative AI systems, such as large language models. Providers must secure government approval before releasing such systems and ensure outputs reflect Core Socialist Values. Content undermining national security or social order is prohibited.
Generative AI Content Labelling (2025)
Beginning in September 2025, all AI-generated content must be clearly labelled. This measure is designed to enhance transparency and public trust, aligning with global concerns over misinformation and authenticity in digital environments.
Mandatory AI Education Initiatives (2025)
Starting from the 2025 academic year, students at all levels will complete at least eight hours of AI education annually. This initiative aims to improve AI literacy, encourage innovation and prepare a workforce capable of navigating and contributing to AI-driven industries.
Crackdown on AI-Generated Misinformation
The China Securities Regulatory Commission has actively addressed AI-driven misinformation in financial markets. In collaboration with law enforcement, it has targeted fraudulent or manipulative content to safeguard investors and preserve market stability.

Balancing Innovation with Control

China’s approach reflects a dual strategy:

Government Oversight: Algorithms and AI systems must undergo review to confirm alignment with state interests, ensuring outputs conform to political and ethical standards.
Education as Regulation: Embedding AI training in the curriculum ensures a tech-literate population that develops AI within the framework of compliance.
Misinformation Safeguards: Specific measures to counter AI-driven disinformation, particularly in finance, demonstrate how regulation is sector-specific as well as systemic.

Comparative Perspective: China, the EU, the UK and the US

China’s framework stands in contrast to the EU’s and UK’s evolving approaches:

China: A centralised, effects-based regime. Binding regulations target specific technologies such as deep synthesis and generative AI. Strict obligations include algorithm filing, security assessments and mandatory content labelling. Innovation is promoted but remains closely tethered to political, ethical and national security standards.
European Union AI Act: A comprehensive, horizontal regulation adopting a risk-tiered system. Prohibited uses (for example, social scoring) are banned. High-risk systems must undergo rigorous conformity assessments, data governance checks and human oversight requirements. General-purpose AI and foundation models are subject to additional transparency and systemic-risk obligations.
United Kingdom: A principles-based, regulator-led model. Without an overarching AI statute, the UK relies on five cross-cutting principles, including safety, transparency, fairness, accountability and contestability — guiding sector regulators such as the ICO, FCA, CMA and Ofcom. Emphasis is placed on proportionate oversight, regulatory sandboxes and assurance frameworks.
United States: A fragmented, sector-driven approach. There is no federal AI law. Instead, federal agencies (FTC, NIST, FDA, CFPB) issue guidance or sector-specific rules and states (such as California and Colorado) enact AI and data-related laws. The Biden Administration’s 2023 Executive Order on Safe, Secure and Trustworthy AI directs federal agencies to develop standards around safety, transparency and accountability. Enforcement relies heavily on existing consumer protection, privacy and anti-discrimination laws rather than a dedicated AI statute.

Global Implications

China’s approach carries significance beyond its borders. By embedding political values and security considerations into its AI rules, China is shaping international debates on transparency, accountability and state control in AI governance. Other jurisdictions — particularly the EU with its AI Act and the UK with its principle-based framework — are likely to look to Beijing’s model when refining their own approaches.

Practical Implications for Businesses

As of late 2025, companies operating across China, the EU and the UK must prepare for increasingly fragmented compliance demands. In China, businesses should ensure algorithm filing, content labelling and government approvals are in place before launching or scaling AI systems. Adopting a compliance-by-design approach that addresses the most stringent obligations across jurisdictions is essential for global players to maintain operational flexibility and regulatory trust.