Unpacking the State-Private Nexus in China's AI Development Path
Key Finding
China’s AI governance is less about top-down authoritarian control and more about a nuanced state–private collaboration where the government acts as investor, regulator, and procurer in dynamic, non-coercive ways
Abstract
The Chinese AI regulatory model has been described as state-driven, where the Chinese government seeks technological supremacy by deploying AI to entrench power through surveillance, control, and cooptation of public and private sectors. It is portrayed as a comprehensive, top-down approach with little room for agency, where autocracy and AI innovation mutually reinforce each other. However, this paper provides a more nuanced picture of China's AI governance. We argue that the Chinese government, at both central and local levels, has adopted a subtle and collaborative approach that integrates state action with private capabilities in dynamic ways that are not necessarily autocratic in nature. We demonstrate this through a framework analyzing the Chinese state's role as investor, regulator, and procurer in relation to private AI companies. First, as an investor, instead of being a controlling shareholder, we find that the Chinese government (or its entities) is a non-controlling shareholder who exerts indirect influence through overlooked mechanisms, while preserving governance powers for corporate boards. Second, as a regulator, contrary to assumptions that regulation is enforced through coercive command-and-control methods, we find that local governments rely on financial support to incentivize AI firms to align with the central government’s objectives. Finally, as a procurer, contrary to the notion that autocracy reinforces innovation through unrestricted data sharing, we show that legal and institutional restrictions apply, and AI firms often have incentives to use non-government data. These findings complexify conventional narratives of Chinese AI governance and offer insights into the evolving state-private relationship, with implications for global AI governance debates.
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© Pangyue Cheng, Ernest Lim, 2025
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