The United States can compete with China for AI leadership while cooperating on specific risks that neither country can manage alone. Competition is about protecting security and technological capacity; cooperation is about reducing dangers that can cross borders. The two approaches can coexist, but neither requires trusting the other broadly—and any agreement needs clear limits, reciprocity, and ways to check whether it is being followed.
Why compete with China on AI?
AI leadership has economic and national-security implications. The U.S. Government Accountability Office (GAO) describes advanced semiconductors and other dual-use technologies as areas of concern because they may contribute to Chinese military systems powered by AI. That is the stated security rationale for controls on sensitive exports; it does not establish that export controls alone determine which country leads in AI.
Restrictions are one part of a broader competition strategy, not a substitute for domestic research, talent, infrastructure, or innovation. Their design involves trade-offs: a control may aim to limit access to a sensitive capability, while also affecting U.S. businesses, allied economies, and the ability to coordinate enforcement. The U.S.-China Economic and Security Review Commission (USCC) recommends assessing control effectiveness while maximizing security impact and minimizing harm to U.S. and allied economies. That is a recommendation, not evidence that any particular control has succeeded or failed.
Competition also reflects different approaches to governance and security. Sandia National Laboratories’ 2025 analysis describes disagreements between the countries over multilateral institutions and the values that AI governance should embody. Those differences make cooperation harder, but do not make every practical agreement impossible.
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Why cooperate if the countries are strategic competitors?
Some AI risks could affect both countries or spread across borders. A serious incident, military miscalculation, or loss-of-control scenario may not respect national boundaries. Even when governments disagree over who should lead, communication and shared technical understanding can help reduce the chance that an incident escalates or that a safety failure goes unnoticed.
Cooperation need not mean sharing sensitive technology, abandoning export controls, or agreeing on a single model of AI governance. It can be bounded by topic and purpose: maintain emergency contacts, discuss military uses, compare safety tests, or conduct research in areas that do not involve national-security-sensitive capabilities. Keeping those channels narrow can make them more feasible than a broad pact based on trust that does not exist.
What cooperation could look like—and what is established
Proposals vary in scope and status. The options below are recommendations or reported discussions unless identified otherwise; they should not be mistaken for operating programs or binding commitments.
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| Option | Potential purpose | Status in the cited sources |
|---|---|---|
| AI emergency communications and incident notification | Give officials a way to communicate about incidents that may have national-security significance and reduce the risk of misreading events. | Associated Press reported in September 2026 that U.S. Treasury Secretary Scott Bessent said the sides had discussed an AI dialogue mechanism and that the U.S. proposed incident notification. The report does not establish Chinese acceptance, a created mechanism, or its terms. |
| Military-AI dialogue | Discuss how AI is used in military settings and where safeguards or communication may reduce risk. | Sandia’s 2025 analysis recommends discussion. It points to a November 2024 agreement on AI use in nuclear command and control, but that agreement should not be read as a comprehensive military-AI framework. |
| Interoperable safety testing and evaluation | Make it easier to compare how systems are evaluated and understand what tests do—and do not—show. | A 2025 Track II consensus document proposes this. It is a dialogue recommendation, not a government commitment or shared testing regime. |
| Research in non-sensitive areas | Explore joint work in areas such as healthcare, biotechnology, and green technology without making national-security-sensitive AI the subject. | The 2025 Track II document proposes such research; it does not establish that joint projects have begun. |
| Expert dialogue and multilateral coordination | Keep technical experts in contact and involve allies or broader scientific networks when bilateral talks are blocked or too narrow. | Sandia recommends leader-level, Track 1.5 and Track 2 engagement, and possible work with allies including the United Kingdom and Japan. In May 2024, the U.S. Commerce Department announced a plan for global cooperation among AI safety institutes and other government-backed scientific offices; that announcement alone does not establish the network’s current membership or activity. |
The distinction between a proposal and an implemented arrangement matters. For example, AP’s September 2026 account attributes to Bessent the statement, “We want a shared vision of common goals and common threats.” That expresses an aim; the report does not show that a mechanism was set up or that China accepted notification obligations. As of that report, the terms, participants, and operational status remained unconfirmed in the cited material.
How to judge a proposed agreement
A useful question is not simply whether the U.S. should cooperate, but whether a particular measure addresses a clear risk at an acceptable cost. Policymakers and readers can assess proposals against these considerations:
- Risk addressed: Does the measure concern military use, cyber misuse, emergency incidents, loss of control, or civilian applications?
- Verification: Can participants observe, test, or otherwise assess whether commitments are being met?
- Reciprocity: Are both governments expected to share relevant information and accept comparable obligations?
- Security and economic costs: Does the measure reduce a specific risk without imposing disproportionate costs on U.S. firms, allies, or research?
- Durability: Could the channel survive worsening relations or a change in political leadership?
- Scope: Is a bilateral arrangement appropriate, or would expert dialogue or multilateral standards be more workable?
These tests also help separate policy tools that serve different purposes. The U.S. could restrict transfers of sensitive compute-related technology while keeping emergency contacts or technical discussions on model evaluation. Whether either step is effective depends on its design and evidence—not on treating competition and cooperation as all-or-nothing choices.
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What U.S. policy documents do—and do not—show
The October 24, 2024 National Security Memorandum on AI is a dated official baseline for the previous administration’s stated objectives on AI leadership, national-security applications, and safety, security, and trustworthiness. It should not be treated as a complete statement of the current administration’s policy. Likewise, a September 2026 Senate committee letter urging frontier-AI guardrails discussions, including a possible mutual pause, records the signatory senators’ advocacy; it is not an adopted executive-branch position.
The cited September 2026 reporting describes possible summit discussions, not a confirmed resulting agreement. It does not establish whether a dialogue or incident-notification arrangement was reached, who would participate, what would trigger notification, what information would be shared, or whether any channel is operational. Those questions should remain open until an official readout or other reliable confirmation answers them.
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