Seeking Deeper: Assessing China’s AI Security Ecosystem
cetas.turing.ac.uk/ Research Report As AI increasingly shapes the global economic and security landscape, China’s ambitions for global AI dominance are coming into focus. This CETaS Research Report, co-authored with Adarga and the International Institute for Strategic Studies, explores the mechanisms through which China is strengthening its domestic AI ecosystem and influencing international AI policy discourse. The state, industry and academia all play a part in the process, with China’s various regulatory interventions and AI security research trajectories linked to government priorities. The country’s AI security governance is iterative and is rapidly evolving: it has moved from having almost no AI-specific regulations to developing a layered framework of laws, guidelines and standards in just five years. In this context, the report synthesises open-source research and millions of English- and Chinese-language data points to understand China’s strategic position in global AI competition and its approach to AI security. This CETaS Research Report, co-authored with the International Institute for Strategic Studies (IISS) and Adarga, examines China’s evolving AI ecosystem. It seeks to understand how interactions between the state, the private sector and academia are shaping the country’s strategic position in global AI competition and its approach to AI security. The report is a synthesis of open-source research conducted by IISS and Adarga, leveraging millions of English- and Chinese-language data points. Key Judgements China’s political leadership views AI as one of several technologies that will enable the country to achieve global strategic dominance. This aligns closely with President Xi’s long-term strategy of leveraging technological revolutions to establish geopolitical strength. China has pursued AI leadership through a blend of state intervention and robust private-sector innovation. This nuanced approach challenges narratives of total government control, demonstrating significant autonomy and flexibility within China’s AI ecosystem. Notably, the development and launch of the DeepSeek-R1 model underscored China's ability to overcome significant economic barriers and technological restrictions, and almost certainly caught China’s political leadership by surprise – along with Western chip companies. While the Chinese government retains ultimate control of the most strategically significant AI policy decisions, it is an oversimplification to describe this model as entirely centrally controlled. Regional authorities also play significant roles, leading to a decentralised landscape featuring multiple hubs and intense private sector competition, which gives rise to new competitors such as DeepSeek. In the coming years, the Chinese government will almost certainly increase its influence over AI development through closer collaboration with industry and academia. This will include shaping regulation, developing technical standards and providing preferential access to funding and resources. China's AI regulatory model has evolved incrementally, but evidence suggests the country is moving towards more coherent AI legislation. AI governance responsibilities in China remain dispersed across multiple organisations. However, since February 2025, the China AI Safety and Development Association (CnAISDA) has become what China describes as its counterpart to the AI Security Institute. This organisation consolidates several existing institutions but does not appear to carry out independent AI testing and evaluation. The Chinese government has integrated wider political and social priorities into AI governance frameworks, emphasising what it describes as “controllable AI” – a concept interpreted uniquely within the Chinese context. These broader priorities directly shape China’s technical and regulatory approaches to AI security. Compared to international competitors, China’s AI security policy places particular emphasis on the early stages of AI model development through stringent controls on pre-training data and onerous registration requirements. Close data sharing between the Chinese government and domestic AI champions, such as Alibaba’s City Brain, facilitates rapid innovation but would almost certainly encounter privacy and surveillance concerns if attempted elsewhere. The geographical distribution of China's AI ecosystem reveals the strategic clustering of resources, talent and institutions. Cities such as Beijing, Hangzhou and Shenzhen have developed unique ecosystems that attract significant investments and foster innovation through supportive local policies, including subsidies, incentives and strategic infrastructure development. This regional specialisation emerged from long-standing Chinese industrial policy rather than short-term incentives. China has achieved significant improvements in domestic AI education. It is further strengthening its domestic AI talent pool as top-tier AI researchers increasingly choose to remain in or return to China, due to increasingly attractive career opportunities within China and escalating geopolitical tensions between China and the US. Chinese institutions have significantly expanded domestic talent pools, particularly through highly selective undergraduate and postgraduate programmes. These efforts have substantially reduced dependence on international expertise, although many key executives and researchers continue to benefit from an international education. Senior scientists hold considerable influence over China’s AI policymaking process, frequently serving on government advisory panels. This stands in contrast to the US, where corporate tech executives tend to have greater influence over AI policy decisions. Government support provides substantial benefits to China-based tech companies. China’s government actively steers AI development, while the US lets the private sector lead (with the government in a supporting role) and the EU emphasises regulating outcomes and funding research for the public good. This means that China’s AI ventures often have easier access to capital and support for riskier projects, while a tightly controlled information environment mitigates against reputational risk. US export controls have had a limited impact on China’s AI development. Although export controls have achieved some intended effects, they have also inadvertently stimulated innovation within certain sectors, forcing companies to do more with less and resulting in more efficient models that may even outperform their Western counterparts. Chinese AI companies such as SenseTime and DeepSeek continue to thrive despite their limited access to advanced US semiconductors.
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