China’s AI Ecosystem: A Background Explainer

Zilan Qian and Kayla Blomquist:

This is a background explainer on China’s AI ecosystem covering the main institutional and commercial actors, how AI policy and regulation are structured, and how frontier AI risk is discussed in China. It is descriptive rather than argumentative and does not make direct policy recommendations. It draws on Chinese-language primary sources for laws, plans, and official statements, and on published analysis for questions of discourse and interpretation. 

Information is current as of 25 September 2026. Several developments discussed in Sections 4 and 5 are recent and still unfolding.

Background

Similar to the US, discussions like the balance between AI development and regulation, AI misinformation, and AI’s impact on labour markets exist in China. However, there is no comparably visible system of competing ideological camps or interest groups in China. 

Three major structural differences between the US and China result in different AI discourse dynamics: 

• The state promotes and restrains AI simultaneously. The state treats AI as both a strategic technology to develop and a source of political, economic, and social risks to manage. The balance between these goals shifts over time, rather than consistently upholding a pro- or anti-AI stance. Chinese AI policy since 2017 has been a recurring tension between development and control.^[1] 
• AI companies are not prominent political actors. Chinese labs or big AI companies do not fund think tanks or run public campaigns. AI researchers in China tend to focus primarily on technical development, with less emphasis than their Silicon Valley counterparts on broader narratives about shaping humanity’s long-term future.^[2]
• Monetization and distribution prospects drive “open” model release practices, which in turn bolster national competitiveness. Chinese developers lean “open” more consistently than their US counterparts, but not uniformly. Firms have increasingly adopted hybrid approaches, releasing some models openly while holding others behind APIs. These decisions are largely driven by prospective routes to revenue and distribution in domestic and international markets, at times reinforced by the stated philosophies of several founders. The state has separately backed the open-source ecosystem, where wide diffusion serves international reputation, discourse power, and global market share.