What Is China’s AI Strategy?

China’s AI strategy is easier to understand if it is viewed as an industrial strategy rather than a product strategy. The country certainly wants competitive models. But official policy goes much further. The central idea is to embed artificial intelligence across the economy. In August 2025, China’s State Council published its AI Plus action plan. The document identifies six broad areas for deep AI integration: science and technology, industrial development, consumption, public wellbeing, governance and international cooperation. CAC

The ambition is unusually explicit. By 2027, the government wants new-generation intelligent terminals and agents to achieve an application penetration rate above 70%. By 2030, the target rises above 90%. By 2035, the plan describes China as entering a new stage of an “intelligent economy and intelligent society.” CAC These are policy targets, not forecasts. They show the intended direction.

Strategy one: move AI into the real economy

China’s policy places substantial emphasis on industrial use. The AI Plus plan calls for AI to be incorporated into corporate strategy, organizational structures and business processes. It specifically highlights design, pilot production, manufacturing, services, operations, industrial software, supply chains and process optimization. CAC This is important because China already has a large physical industrial base.

AI therefore has a natural route into factories, robotics, logistics, electric vehicles, agriculture and industrial equipment. The strategy is not simply to create software companies around AI. It is also to make existing industries more intelligent.

Strategy two: build the compute underneath it

Large-scale AI requires computing infrastructure. China’s policy explicitly calls for breakthroughs in AI chips and enabling software, ultra-large intelligent-computing clusters, better national allocation of computing resources and closer coordination between data, compute, electricity and networks. CAC This focus has become more important as access to advanced foreign semiconductors has tightened. U.S. export controls target advanced computing chips, high-bandwidth memory and semiconductor-manufacturing equipment linked to advanced AI capabilities. Bureau of Industry and Security

China’s domestic-compute push is therefore both an economic objective and a response to supply-chain constraints.

Strategy three: make agents a mass technology

China has unusually explicit national targets around agents. The State Council plan does not treat them as a niche enterprise-software category. Agents appear across industrial services, consumer experiences, government services and new forms of work. CAC In May 2026, Chinese authorities also issued implementation guidance specifically around the standardized application and innovative development of agents, tying the initiative back to the national AI Plus program and its 2027 adoption target. CAC

That suggests China sees agents as a potential general interface between models and economic activity.

Strategy four: support open-source ecosystems

China’s national plan explicitly calls for stronger AI open-source communities, open models, tools and datasets, and projects with international influence. CAC This is commercially important. Open-weight Chinese models can spread internationally even when Chinese cloud platforms or consumer apps do not. That allows the model layer to become part of global infrastructure. Stanford’s 2026 AI Index shows that Chinese frontier models have already become technically competitive with leading U.S. systems by several major benchmarks. Stanford HAI

Strategy five: connect AI to hardware

China’s policy also targets intelligent connected vehicles, AI computers and phones, smart robots, wearables, smart homes, drones and other intelligent devices. CAC This is another place where the industrial base matters. The convergence of AI with robotics, manufacturing and embedded computing turns model capability into physical products. AI becomes less visible as a standalone service and more embedded into machines.

Strategy six: combine deployment with governance

It would be inaccurate to describe the official strategy as growth without governance. The same AI Plus document calls for risk monitoring, safety evaluation, regulatory development, model and infrastructure security, and measures addressing hallucinations, discrimination and black-box behavior. CAC China’s governance model differs institutionally from Western approaches, but safety and control are explicit components of the published policy.

How this differs from the United States

The U.S. AI Action Plan is also broad, but its policy emphasis is different. The American plan foregrounds rapid innovation, private-sector development, data-center and semiconductor infrastructure, reduced regulatory barriers, and exporting U.S. technology stacks internationally. The White House China’s plan puts heavier explicit emphasis on coordinated diffusion across industry and society. That does not mean the U.S. does not care about adoption or China does not care about frontier research. Both do. The difference is in emphasis and institutional structure.

Mindzy perspective

The most important lesson from China’s strategy is that AI is being treated as infrastructure for the wider economy. The model is only one layer. Behind it sit chips, compute, energy and data. In front of it sit agents, enterprise software, industrial systems, robots and consumer products. That full-stack view is increasingly relevant to companies too. The competitive advantage will not come simply from having access to a powerful model. It will come from integrating intelligence into the systems where real work already happens.

Key takeaways

• China’s AI strategy links model development to manufacturing, robotics, public services and consumer products.
• The plan treats compute, data, energy and open ecosystems as national infrastructure.
• Its success will depend on operational deployment rather than benchmark leadership alone.

Sources

1. CAC
2. Stanford HAI
3. IEA