The United States is expanding its AI infrastructure while relying on global supply chains that include China-linked sources for some critical minerals and batteries. That does not mean U.S. AI companies all depend on Chinese suppliers, or that available trade data proves a direct Chinese-company dependency for U.S. frontier AI hardware. The evidence points to a more specific tension: AI competitiveness spans far more than model development, and vulnerabilities in materials processing and battery production can matter even when servers and chips are assembled elsewhere.
What “winning the AI race” actually means
AI competitiveness is not a single leaderboard. It can refer to research, the ability to deploy AI, the workforce and investment that support it, computing infrastructure, or influence over laws and standards. A comparison between the United States and China needs to specify which outcome it measures.
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The U.S. Government Accountability Office’s May 2026 framework groups competitiveness into four connected pillars:
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- Human capital: the talent and workforce needed to develop and use AI.
- Governance: laws, policies, and other rules shaping development and deployment.
- Economy: investment, financing, and the computing infrastructure that supports AI work.
These factors interact, and their importance depends on the policy question being asked. The framework also calls attention to risks such as job dislocation and rising energy use. As GAO puts it, “The complexity of factors affecting AI competitiveness makes it difficult to decide which factors are more important than others.”
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AI infrastructure is part of a global trade network
Building data centers and computing systems involves equipment and parts that cross borders. In a February 2026 analysis, the Federal Reserve Board tracked three customs categories as a proxy for AI-related trade: processing units (HS 8471.50), other data-processing units (HS 8471.80), and parts and accessories of data-processing machines (HS 8473.30). Examples include servers, server baseboards, and graphics cards.
The Board counted more than $272 billion in global trade across those categories in the first half of 2025, 65% more than in the first half of 2024. This is not the total value of the AI industry, nor is it a measure of U.S.–China bilateral trade. The categories may include products not used for AI and leave out AI-related goods classified elsewhere.
The Federal Reserve reported that the United States and China drove growth in imports in these categories in 2024. U.S. imports accelerated in 2025; Chinese imports fell in the second quarter amid geopolitical tensions and restrictions. Mexico’s imports also rose from a low base as it assembled high-tech hardware for the U.S. market, with a significant portion of its AI-related imports coming from Taiwan. These customs figures describe trade in selected product categories; they do not identify the suppliers to individual AI companies.
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Where China-linked supply exposure is best documented
The clearest evidence in the available government and congressional reports concerns selected minerals and batteries. These are important parts of the broader technology economy, but they are not a direct measure of how much of U.S. AI hardware comes from Chinese firms.
Critical minerals and processing
GAO’s July 2026 assessment says U.S. batteries and semiconductors rely heavily on imported minerals, including lithium, gallium, and germanium. It reports that China owns 99% of worldwide gallium production. Gallium is used in semiconductors, making its concentrated supply a specific point of exposure—not proof that China supplies every semiconductor input.
A January 2026 White House proclamation states that, as of 2024, the United States was 100% net-import reliant for 12 critical minerals and at least 50% net-import reliant for 29 others. Net-import reliance is not the same as having no domestic mining: extraction at home does not guarantee that refining and processing also happen domestically. The proclamation describes U.S.-mined, unprocessed rare-earth oxides being sent abroad for refining and then reimported, as well as reliance on imported permanent magnets.
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The distinction is consequential. The White House’s proclamation states: “Mining a mineral domestically does not safeguard the national security of the United States if the United States remains dependent on a foreign country for the processing of that mineral.” Mining, refining, component-making, and final assembly are separate stages; domestic activity at one stage does not establish a domestic supply chain end to end.
Batteries
The U.S.-China Economic and Security Review Commission’s November 2024 chapter describes China’s strength across the battery chain, from mining and processing raw materials to component fabrication and finished batteries. Its figures are historical and use different measures:
| Measure | China | United States | Period and source |
|---|---|---|---|
| Share of global battery production capacity | 77% | 6% | 2022; U.S.-China Economic and Security Review Commission, 2024 report |
| Share of U.S. lithium-ion battery imports by value | More than 70% | Not stated in the cited report figure | 2023; U.S.-China Economic and Security Review Commission, 2024 report |
The first row compares production capacity, not batteries actually produced or imported. The second concerns the value of U.S. imports, not their volume or the current share. The commission also reported that six of the world’s ten largest battery producers were based in China and accounted for the 77% capacity share in 2022.
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What these figures do—and do not—show about U.S. AI
Taken together, the sources show a U.S. AI build-out embedded in international trade and a concentrated China-linked role in selected critical minerals and batteries. They do not provide a single percentage for “U.S. AI dependence on China.” The Federal Reserve’s customs categories are imperfect proxies for AI-related equipment trade, while GAO and the commission document particular mineral and battery exposures. None of these measures maps the suppliers used by individual U.S. AI firms or quantifies Chinese-company inputs in specific data centers or frontier chips.
There is also a separate, non-physical concern. In September 2026, the National Security Agency announced a joint advisory with the FBI and CISA alleging that China-based companies used industrial-scale distillation campaigns against U.S. frontier AI models. The agencies said distillation can be a legitimate research technique but alleged misuse in the campaigns described. That is an allegation about access to model capabilities, not evidence of mineral sourcing, hardware imports, or physical supply-chain dependence.
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There is no single timeline for reducing reliance: recycling, substitution, domestic processing, and new manufacturing address different stages and face different constraints. GAO’s July 2026 assessment distinguishes options that may help sooner from those that require longer development.
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Recycling and collection
GAO describes battery-recycling technology as mature, but says the United States lacks sufficient collection and recycling infrastructure and often exports battery-recycling material for processing. Recycling could contribute to reducing dependence in roughly two to three years, subject to building out that infrastructure. This is a possible contribution, not a guarantee that imports can be replaced on that timetable.
Substitution depends on the application
Lithium iron phosphate batteries can reduce reliance on cobalt, manganese, and nickel for stationary grid storage. Their lower energy density makes them less suitable for some other uses, including long-haul electric vehicles. Lithium-free batteries are not yet commercially mature.
For semiconductors, GAO says recycling and material substitution are likely years away from maturity. Potential substitutes for minerals such as gallium and indium do not yet perform as well under relevant conditions. Recovering materials from electronic waste is difficult because quantities are small and materials are mixed or bonded together.
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Domestic capacity takes sustained investment
GAO identifies research and testing, domestic manufacturing capacity for substitute technologies, and better systems for collecting, sorting, transporting, and storing scrap and end-of-life devices as policy options. Facilities can be costly and specialized, and new infrastructure can take a decade or more. A near-term recycling opportunity and a long-term processing-capacity challenge therefore cannot be treated as interchangeable solutions.
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