Executive Summary
The current pathway to breakthrough artificial intelligence (AI) capabilities relies on amassing and leveraging vast “compute”—specialized chips housed within massive data centers that generate the computational power to train, enhance, and deploy advanced models. If current AI development trends continue, securing and extending U.S. access to a robust compute ecosystem will play a decisive role in whether the United States leads the world in AI or cedes its leadership to competitors. The nation that leads in deploying compute worldwide will wield critical leverage over the rules and norms governing its use. Most importantly, U.S. leadership can crowd out China’s expanding sphere of technology influence and ensure the AI transition is underpinned by trusted democratic technologies. This goal necessitates a strategy with two key components: maintaining U.S. control of the most capable compute infrastructure in the world to ensure leadership at the AI frontier, while simultaneously providing subfrontier levels of compute to partners around the world.
Recent advances in AI efficiency, as demonstrated by Chinese AI models like DeepSeek-R1, have not negated the fundamental importance of compute for AI leadership. The nation with the most robust compute ecosystem will retain key advantages: the ability to train the most advanced systems, enhance and deploy those systems at scale, and run the experiments necessary to drive new breakthroughs in model efficiency and training. These advantages are likely to generate a self-reinforcing cycle of AI development, making it increasingly difficult for other nations to close the gap. If current technical trends hold, and as chip export controls increasingly hinder China’s capabilities, the AI capability gap between the United States and China should widen. However, the United States cannot afford to be complacent.
Washington’s efforts to protect America’s AI leadership have relied heavily on controlling the export of advanced AI chips. Controls on semiconductor manufacturing equipment going to China were imposed as early as 2019, followed by AI chip export controls targeting U.S. adversaries in 2022, which were strengthened in 2023, 2024, and 2025. In January 2025, the Biden administration’s Framework for Artificial Intelligence Diffusion went a step further, placing caps on compute exports to most countries in the world. While now rescinded, this unprecedented action sent a clear signal to other nations that the United States is willing and able to control AI compute access. However, a heavily protectionist approach faces challenges. Abroad, chip smuggling has provided China with illegal access to advanced chips, eroding the U.S. lead. At home, permitting and regulatory constraints threaten to limit America’s ability to meet the energy demand for large-scale AI data centers and chip fabrication. Nondemocratic countries that possess the regulatory flexibility, capital, and readily available energy now seek to rapidly build frontier-scale AI data centers, with the potential to surpass the United States’ own compute ecosystem, absent adequate safeguards. Meanwhile, China’s ongoing investments in its compute capacity could eventually create a viable alternative supply chain beyond U.S. control, while growing concerns over reliance on U.S. technology among traditional partners may fuel demand for non-U.S. compute offerings.
In light of these headwinds, this report argues for a more proactive “promote” approach to global compute provision to sustain and strengthen long-term U.S. AI leadership. The Trump administration has already taken significant steps in this direction, announcing major AI partnerships with the United Arab Emirates and the Kingdom of Saudi Arabia in May 2025. However, these initiatives should be integrated into a comprehensive AI diplomacy strategy that balances several strategic objectives:
Keeping the frontier of AI training in the United States and its closest allies to identify, leverage, and secure the most groundbreaking AI capabilities in a way that supports U.S. national security;Preventing China from accessing U.S. and allied AI compute capabilities that could confer meaningful military or strategic advantages or strengthen authoritarian regimes; andReinforcing the United States’ position as the AI partner of choice, expanding its global compute footprint and drawing swing states more closely into the U.S. orbit through deeper technology partnerships.
To achieve these objectives and advance America’s long-term AI leadership, the report makes the following recommendations to the U.S. government:
“It is not enough to seek to protect America’s technological lead. We also have a duty to promote American technological leadership.”
Michael Kratsios, director of the White House Office of Science and Technology Policy
The United States faces a choice: leverage its current lead to promote U.S. AI infrastructure and applications globally, while preserving its edge at the frontier; or continue to primarily focus on protection, while other countries gradually narrow the gap. As Michael Kratsios, President Donald Trump’s science and technology advisor, put it: “It is not enough to seek to protect America’s technological lead. We also have a duty to promote American technological leadership.” The protect and promote strategy outlined in this report offers a path to sustainable leadership that both safeguards critical capabilities and expands American influence in the global AI ecosystem.
Introduction
In March 2025, President Donald Trump wrote to Michael Kratsios, the director for the White House Office of Science and Technology Policy, to ask a momentous question: “How can the United States secure its position as the unrivaled world leader in critical and emerging technologies—such as artificial intelligence . . . ?”10 This question reflects a growing consensus in Washington and capitals around the world that the nation that leads the world in advanced artificial intelligence (AI) will pioneer new scientific breakthroughs, unlock powerful military and intelligence capabilities, and turbocharge economic competitiveness. Although there is ongoing debate about the best pathway to long-term AI progress, large-scale AI models show the most transformative promise. Historically, AI systems were specialized, with training data narrowly tailored to their intended function. Now, leading foundation models—which ingest vast collections spanning trillions of words from diverse sources—currently perform as well as purpose-built systems in specialized domains, as well as across general-purpose tasks. The United States leads the world in large-scale AI development, driven in part by its leading talent and innovation ecosystem, but also by its access to cutting-edge “compute”—the specialized chips, data centers, and infrastructure needed to train and deploy the most capable AI systems.
But U.S. AI leadership is not guaranteed. The release of DeepSeek-R1, the first highly capable reasoning model from a Chinese firm, demonstrated China’s capacity to apply breakthroughs in algorithmic efficiency to do more with fewer chips in the face of U.S. export controls. DeepSeek released R1 a little more than four months after OpenAI released its o1 model, with approximately the same performance. It is widely believed that DeepSeek-R1 leveraged OpenAI’s know-how, whether through training a new model from the o1 model’s outputs in a process known as “distillation,” or through informal conversations at Silicon Valley parties. This highlights the inherent difficulty of controlling the spread of technical knowledge and expertise. In light of China’s advancements, the U.S. government needs a clear strategy for protecting and enhancing its AI edge, and compute is one of its best levers available. Unlike algorithms and know-how, compute is physical, with a narrow, specialized supply chain, making it significantly more controllable through policy.
Compute has become the engine of AI progress, with advanced chips and massive data centers enabling breakthroughs in AI capabilities and large-scale deployment. Although algorithmic progress is allowing AI models to become far more efficient—the compute needed to train models of equivalent capability drops by half every eight months—the availability of compute still drives the sophistication and scale of their deployment. Critically, advancing the AI frontier continues to require exponentially more compute resources. All of this underscores the strategic imperative of maintaining and sustaining America’s edge in compute. In an age of escalating technology competition, nations with robust compute ecosystems will likely command a significant advantage in both AI development and deployment.
The United States’ approach to preserving its AI compute advantage has historically relied heavily on export controls—an inherently restrictive measure. These controls have sought to solidify America’s advantage over China and other competitors by limiting their access to advanced AI chips. This has allowed the United States to continue to lead in AI data center build-outs. But this strategy faces mounting challenges: overreliance on restrictive measures risks alienating allies and encouraging the rise of alternative AI supply chains. The People’s Republic of China (PRC) is investing to indigenize AI semiconductor production, including close to $100 billion through its state-owned National Integrated Circuit Industry Investment Fund. Domestically, U.S. companies face constraints in energy availability, which hinders their ambitions to deploy large-scale computing infrastructure. Even traditionally close partners are growing skeptical of Washington’s expanding use of economic tools for national security objectives, with even close allies calling for non-U.S. AI compute.
Faced with these headwinds, the current U.S. lead may be short-lived. It is therefore imperative for policymakers to think strategically about how to leverage this advantage now to shape the global AI ecosystem. Washington needs a more proactive “promote” approach to turn its short-term lead into an enduring advantage, without allowing competitors to leapfrog the United States in AI compute.
The Trump administration has commenced decisive action on this front, announcing major AI partnerships with the United Arab Emirates and the Kingdom of Saudi Arabia in May 2025. The United Arab Emirates agreement includes plans for a five-gigawatt (GW) AI campus in Abu Dhabi and a deal for the United States to enable the import of 500,000 advanced NVIDIA AI chips annually, while the Saudi Arabia deal includes over $80 billion in cross-border AI investments through multiple company-to-company agreements. While the details—and security measures—are still being developed, these initiatives represent a significant shift toward using AI partnerships as instruments of strategic competition, demonstrating a new willingness to deploy compute resources as tools of technological diplomacy rather than merely restricting access to competitors.
U.S. policy settings now need to catch up. Beyond individual deals, U.S. AI leadership requires moving from a policy of global restriction and control to responsible deployment and diffusion, accompanied by security measures and safeguards. Only then can the United States appropriately manage emerging national security threats from foreign and domestic AI progress and ensure democratic leadership of the global AI ecosystem.
This report outlines the ongoing importance of compute for the development and deployment of AI—even in the face of increasingly cost-efficient models. It articulates the national security rationale for active efforts to maintain and strengthen U.S. AI leadership. Assessing compute governance actions to date, it argues for a more proactive U.S. approach to global compute provision, shifting from purely protecting U.S. technology to a strategy of promotion and AI diplomacy, underpinned by partnerships with strategic countries. This report lays a path for near-term engagements, identifying six priority nations to engage with based on strategic importance, compute needs, and alignment potential: the United Arab Emirates, Saudi Arabia, Brazil, India, and AUKUS partners (Australia and the United Kingdom). The report sketches out next steps for advancing these critical partnerships, while strengthening controls on adversaries such as China. Finally, this report evaluates the role of multilateralism in sustaining and supporting U.S. AI leadership and makes a series of recommendations to inform American AI leadership.
Ultimately, AI and its impacts will transcend national borders. But the infrastructure that underpins it will remain firmly rooted in the physical world. The United States has a choice: proactively promote its AI globally to maintain technological leadership and shape the rules of AI development, or risk watching its advantage erode as competitors build alternative ecosystems that diminish America’s power to manage AI opportunities and risks and ensure U.S. security and prosperity.