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China’s AI Strategy Is More Than a Race for Better Models
China is positioning itself as an advocate of open, sovereign AI while using rare earth leverage and PLA “intelligentization” to compete with U.S. Beijing’s strategy operates across governance, models, chips and minerals, infrastructure, and military information systems—not only the public contest over chatbot bench...
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Key takeaways
- China is positioning itself as an advocate of open, sovereign AI while using rare earth leverage and PLA “intelligentization” to compete with U.S.
- Beijing’s strategy operates across governance, models, chips and minerals, infrastructure, and military information systems—not only the public contest over chatbot benchmarks.
- Available evidence supports PLA experimentation and integration in surveillance, training, logistics, command support and target recognition, but not a verified, fully autonomous Chinese AI kill chain.
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openai.comCreate a landscape editorial hero image for this Studio Global article: How is China positioning itself against perceived U.S. AI dominance and “weaponisation” of AI—through advocacy of open-source AI, leveraging. Article summary: China is pursuing a dual strategy: present itself as the champion of accessible, sovereign and non-exclusive AI—especially for developing countries—while building national leverage across the AI stack and embedding AI in. Topic tags: general, government, news, general web, education. Style: premium digital editorial illustration, source-backed research mood, clean composition, high detail, modern web publication hero. Use reference image context only for broad subject, composition, and topical grounding; do not copy the exact image. Avoid: logos, brand marks, copyrighted characters, real person likenesses, fake screenshots, UI text, readable text, watermarks, c
China’s response to perceived U.S. AI dominance is a broad strategic package rather than a single technology program. Beijing is promoting an alternative vision of global AI governance centered on openness and digital sovereignty, building leverage through critical-mineral controls, and pursuing military “intelligentization.” At the same time, the narrow gap between leading U.S. and Chinese models has made the competition look far closer at the model layer than the investment totals suggest. 36
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The central message: AI should not be controlled by one bloc
China’s diplomatic pitch presents AI as a shared technology that should not be monopolized by a single country or governed through rival camps. In 2025, Premier Li Qiang proposed a global AI cooperation organization and said China wanted to help coordinate regulation and share its advances. 37 In July 2026, Xi Jinping used the World Artificial Intelligence Conference to promote open-source technology and a China-led AI cooperation framework as an alternative to U.S.-led influence over AI rules.
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This framing is directly relevant to countries deciding which technical ecosystems, cloud services, standards and governance arrangements to adopt. Chinese officials have also argued for countries’ “digital sovereignty” and opposed being forced to take sides in the AI race. 34
Open-source or open-weight AI is useful to this strategy because it gives Beijing a practical complement to its political message: models that can be downloaded, adapted, and deployed outside a U.S.-proprietary platform. But the messaging should not be confused with technological independence. Access to advanced chips, semiconductor tools, cloud infrastructure and capital remains a separate—and consequential—contest.
Rare earths are Beijing’s counter-leverage
Washington’s restrictions on China have focused heavily on advanced semiconductors and related technology. Beijing’s strongest reciprocal pressure point lies further down the industrial supply chain: critical minerals and processing.
China introduced two waves of rare-earth export controls in April and October 2025. The European Parliament’s research service reports that the second wave was suspended until November 2026. 1 These measures do not give China control over AI software or frontier-model development. They can, however, affect supply chains used by high-technology and defense industries, where rare earths and magnets are important inputs.
That makes minerals a form of bargaining leverage in a wider struggle over technology access. A U.S.-China Economic and Security Review Commission report warns that targeted Chinese restrictions could disrupt high-tech sectors, including AI and data-center infrastructure. 2 The key point is not that either side holds an absolute choke point. It is that chips and critical minerals have become reciprocal sources of pressure in a relationship that still contains substantial interdependence.
PLA AI modernization is about information advantage
The military dimension is often described as PLA “intelligentization”: integrating AI alongside mechanization and informatization. The PLA’s 2027 modernization objective includes accelerating the integrated development of all three. 18
PLA thinking treats information superiority as fundamental to campaign success. Research on Chinese military AI links this information-centric approach to “system destruction warfare”: disrupting critical networks, sensors, command systems and other nodes that enable an adversary’s forces to function as a system. 20
Public research and procurement evidence points to several priority areas:
- intelligence, surveillance and reconnaissance;
- intelligent or autonomous vehicles;
- predictive maintenance and logistics;
- information and electronic warfare;
- simulation and training;
- command-and-control support; and
- automated target recognition.
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The U.S. Defense Department similarly assesses that China is prioritizing AI-enabled capabilities because it views AI as part of a new revolution in military affairs, while seeking to draw on commercial-sector developments. 19
What “AI-enabled targeting” does—and does not—show
AI can support military targeting without independently deciding to use force. In practice, the relevant functions may include processing sensor data, recognizing potential targets, prioritizing information, supporting commanders, allocating resources, and improving planning or simulation.
The evidence provided supports doctrine, procurement, research, and enabling uses across those functions. It does not establish that the PLA has fielded a mature, autonomous end-to-end kill chain or delegated lethal decisions to AI. That distinction matters: the military modernization effort is real, but it is an ongoing transition rather than proof of fully autonomous operational capability. 17
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Why the model race is much tighter than the investment race
Stanford’s 2026 AI Index illustrates the apparent contradiction at the heart of U.S.-China AI competition. U.S. private AI investment reached $285.9 billion in 2025, compared with $12.4 billion in China—more than a 23-fold difference. Stanford notes that private-investment figures may understate China’s total spending because they exclude government guidance funds. 50
Yet the leading models have been much closer than those investment totals imply. Stanford reports that U.S. and Chinese models traded the lead multiple times from early 2025; DeepSeek-R1 briefly matched the top U.S. model in February 2025, and the leading U.S. model was ahead by only 2.7% in March 2026. 50
That is evidence of rapid convergence at the frontier-model level, not evidence that the two countries possess equivalent AI systems. The United States still has major structural advantages in private capital and in producing notable models: U.S.-based institutions produced 40 notable AI models in 2024, compared with 15 from China. 49
Benchmark convergence is not stack-wide parity
Model rankings are only one layer of national AI power. The broader contest includes:
- models and applications, including the availability and adoption of open models;
- compute and semiconductors, including access to advanced chips and manufacturing technology;
- industrial supply chains, where minerals and materials can become leverage;
- military systems, especially intelligence, command support, simulation, logistics and precision-planning tools; and
- global governance and infrastructure, where competing blocs seek influence over standards, partnerships and deployment.
China’s approach is therefore best understood as an effort to reduce dependence on U.S.-centered technology while making China a viable alternative partner for AI development and governance. Its open-AI rhetoric, rare-earth controls and military AI agenda are connected by that objective, even though they operate on different timelines and have different practical limits.
The strategic implication: a reinforcing security dilemma
Each side portrays its own restrictions as defensive and the other side’s behavior as coercive or destabilizing. The predictable response is greater self-reliance: more domestic technology development, more supply-chain diversification, more alliance-building, and more military integration of commercial AI advances.
For businesses and governments, the durable lesson is that U.S.-China AI competition cannot be assessed solely by comparing the best available models. A 2.7% performance gap is a meaningful sign of competitive pressure, but it does not erase U.S. advantages in investment and model production—or China’s capacity to shape access through industrial supply chains and to pursue AI-enabled military modernization. 49
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What is the short answer to "China’s AI Strategy Is More Than a Race for Better Models"?
China is positioning itself as an advocate of open, sovereign AI while using rare earth leverage and PLA “intelligentization” to compete with U.S.
What are the key points to validate first?
China is positioning itself as an advocate of open, sovereign AI while using rare earth leverage and PLA “intelligentization” to compete with U.S. Beijing’s strategy operates across governance, models, chips and minerals, infrastructure, and military information systems—not only the public contest over chatbot benchmarks.
What should I do next in practice?
Available evidence supports PLA experimentation and integration in surveillance, training, logistics, command support and target recognition, but not a verified, fully autonomous Chinese AI kill chain.