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China’s AI strategy pairs domestic control with global diffusion, aiming to lead innovation, standards and governance on its own terms
China's 15th Five-Year Plan positions artificial intelligence as central to its industrial strategy, aiming to drive productivity gains necessary to offset structural economic deceleration and demographic challenges. AI is identified as a 'new quality productive force' to foster technology-driven growth, extending beyond industrial automation to service sectors like healthcare and education. This ambition includes the development of artificial general intelligence. The global pursuit of AI leadership for economic competitiveness is a shared imperative for the US and the EU, highlighting AI's role in addressing their own economic challenges and securing digital infrastructure.
A crucial driver for China's AI strategy is the imperative to reduce technological dependency, particularly in critical components for AI infrastructure, a vulnerability exposed by US export controls on advanced semiconductors. President Xi Jinping has called for national mobilisation to achieve 'self-reliance and self-strengthening' and to build an 'independent and controllable' AI ecosystem using domestic hardware and software. This internal focus is complemented by external engagement, where China encourages the global adoption of its AI platforms to expand its ecosystem and assert its leadership in global AI development. The US faces its own sovereignty challenge with concentrated advanced semiconductor manufacturing in Taiwan, while Europe remains highly dependent on foreign cloud providers and chip fabrication.
The third and often less publicly discussed objective for China's AI push is the enhancement of its military capabilities. AI is already being integrated into autonomous systems, intelligence analysis, logistics, and battlefield decision support by both US and Chinese armed forces. While the US currently leads in military-AI investment, China is strategically integrating civilian technological and industrial capacities with military research, procurement, and production to develop an 'AI-enhanced military'. In contrast, Europe's military-AI capabilities are fragmented, though recent rearmament efforts are beginning to stimulate defence-related AI investment.
China's AI approach is characterized by a state-coordinated innovation ecosystem, where planning, industrial policy, infrastructure investment, and targeted regulation are harmonized across the entire AI technology stack. This includes direct and substantial state financial support for chip manufacturing through initiatives like the National Integrated Circuit Industry Investment Fund. For model and application development, Beijing offers compute subsidies and government guidance funds, effectively directing private capital. Domestic firms also benefit from regulatory barriers that shield them from foreign generative-AI service providers. China's strategy of publishing open-weight AI models globally facilitates adoption, localises user data, and crowdsources improvements, serving as a competitive tool to reduce reliance on foreign intellectual property and to shape global standards, which may lead to new dependencies for European firms.
The United States adopts a distinct AI strategy primarily driven by the private sector, where innovation is enabled rather than directly controlled by authorities. Investment in AI hardware and infrastructure is heavily concentrated among a few large tech firms like NVIDIA, Alphabet, Amazon, Meta, Microsoft, and Oracle, whose capital expenditure fuels AI divisions that might otherwise be unprofitable. Government intervention focuses on defence procurement, basic research, export controls (to limit China's access to advanced AI chips), and regulatory frameworks, though there has been a recent shift towards deregulation. This private-sector-led approach, however, carries risks, including the potential for private investors to demand quicker returns and the strain that rapid compute build-out places on public electricity grids.
Europe's strategy in AI is unique, marked by its development of the world's most comprehensive AI governance framework, the EU AI Act. This risk-based regulation bans harmful AI uses and imposes strict conditions on high-risk systems, complementing policies aimed at fostering innovation. However, this regulatory leadership has not yet translated into a significant surge in innovation or widespread adoption, partly due to compliance costs and regulatory uncertainties. While the EU is pursuing regulatory simplification and various initiatives to boost AI infrastructure, it struggles to finance a coherent industrial policy needed to bridge the gap with the US and China, remaining dependent on foreign cloud providers and advanced chip fabrication.
China's AI strategy is highly effective and resourceful, combining state support for leading enterprises, directed computing power, a protected domestic market, and the global promotion of its open-weight models within a cohesive framework. In contrast, the US relies on a market-driven approach, powered by substantial private investment, supplemented by government funding for research and strategic export controls. For Europe, the primary challenge lies in its ability to translate its ambitious AI goals into unified and rapid actions, particularly in developing a coherent industrial policy to close the technological divide with its global competitors.