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In the global race for technological dominance, the United States risks undermining its own advantage by focusing more on restrictions than renewal. The most recent example came this week when the Trump administration blocked Nvidia’s H20 chips—designed specifically to comply with earlier export rules—from being sold to China. These tactical actions might buy time, but they are not a grand strategy.
If America wants to maintain its edge over China, the answer isn’t more barriers—it’s building more bridges. The United States should seek to retain global talent, expand educational opportunity, develop research infrastructure, and enhance public understanding of how artificial intelligence (AI) actually works to maintain its lead in the ongoing technology competition with the Chinese Communist Party.
Export Controls Can’t Substitute for National Renewal
The new export restrictions on Nvidia’s H20 chips shut down one of the last legal channels for AI hardware exports to China. The H20, by design, limited interconnect bandwidth and processing power to remain beneath U.S. Department of Commerce’s thresholds targeting military-use AI accelerators.
Restricting access to technology is a delaying action at best. Winning the long-term contest over who shapes the future of AI depends on something more fundamental: who can develop talent, deploy infrastructure, and democratize innovation.
Five Actions to Win the Tech Race
There are five immediate steps the Trump administration could take to sustain America’s advantage in the AI race.
- Fix immigration to retain the world’s best minds.
AI’s global talent pool wants to come to the United States—but these individuals increasingly can’t stay in the country. According to the National Center for Science and Engineering, over 57 percent of doctoral candidates and 46 percent of master’s candidates in computer science and mathematics are foreign-born. Yet, President Trump has signaled he could crack down on foreign visas and is pulling funds from top research universities in the United States. The net result is that foreign talent, even if they can travel to study and work in the United States, may seek out other options. This means it is time to fix a broken immigration system. In fact, multiple legislators have signed on to bipartisan legislation to keep talented international students. Attracting and retaining tech talent should be a priority for broader bipartisan immigration reform.
The United States needs an immigration system aligned with national security and economic growth that caters to high-skilled individuals. Strategic competition starts with strategic talent retention.
- Invest in STEM education and AI literacy—from K–12 to PhDs.
Education is central to national security and economic prosperity. OECD research finds that higher levels of education—especially in science, technology, engineering, and mathematics (STEM)—directly correlate with greater national productivity and innovation. Furthermore, a study by the Economic Policy Institute concludes that investments in education significantly contribute to long-term GDP growth.
Yet, U.S. STEM proficiency remains alarmingly low: Only 30 percent of students meet science proficiency standards. The United States needs national STEM mobilization, perhaps modeled on Cold War–era investments, to improve public school pipelines, expand access to courses in computer science as well as the underlying math that drives machine learning, and support under-resourced districts.
And it’s not just about getting more students into STEM majors. Every American should understand how AI works—not just what it does. A public that understands how AI functions is less vulnerable to misinformation and better equipped to contribute to its responsible development.
- Democratize access to high-performance computing.
High-performance computing (HPC) is a mix of art and science for applying computational power to perform complex calculations, simulations, and modeling tasks that eclipse the capabilities of standalone desktops. This computational power is central to training AI/ML algorithms as well as other critical capabilities for a twenty-first-century economy, such as creating digital twins and making detailed weather forecasts. But most student researchers and public universities lack access to the compute power available to large technology firms and government researchers.
In the twenty-first century, HPC is critical infrastructure. A national network of shared, affordable, and secure HPC environments—especially in land-grant institutions—would unlock a new generation of AI innovation from the bottom up. There are historical antecedents. Multiple innovators over the last two generations in America stress the importance that early access to computational technology had on their thinking and subsequent businesses. For example, Microsoft founders Bill Gates and Paul Allen had access as teenagers to an early computer and experimented with pioneering computer code—BASIC—developed at Dartmouth University. Cold War investments in universities and K-12 education paid massive dividends in the rise of modern technology companies.
- Execute the federal AI strategy.
The White House’s new Office of Management and Budget guidance is a great start toward aligning the federal government on the implementation of AI. It requires agencies to appoint chief AI officers, audit their AI systems, and improve transparency. But guidance is not execution.
The United States needs agency-by-agency experimentation teams, AI red-teaming cells, and data modernization programs to transform public-sector performance and trust. The U.S. government can become a model for responsible, effective AI governance—if it commits to implementation. This effort should show how public policy can be a public good and create incentives for AI innovation across American society.
- Double down on public innovation funding.
From DARPA’s early investments in the internet to the National Science Foundation’s funding of early AI research, federal science funding has built the foundation for every major tech wave in the past 50 years. This legacy must continue. Could these investments be more efficient and better align the public and private sector? Almost certainty. Yet, there is no substitute for government-subsidized basic research that helps scientists assume risk and explore new ideas before businesses determine what is (and is not) profitable. Seen in this light, recently announced cuts to science funding could jeopardize U.S. technological competitiveness.
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Strategy Is More than Scarcity
The United States will not win the AI competition by restricting others from accessing technology. It will win by making sure more of its own citizens and institutions can build, understand, and govern emerging technologies like AI.
Export controls are the blunt instrument of a defensive posture. The offensive strategy—the one that wins—is built on education, inclusion, and infrastructure. President Trump has an opportunity to pursue this course and guarantee America remains the world’s leading AI superpower. No amount of export controls will make up for a broken education and immigration system and cuts to science funding.
Benjamin Jensen is director of the Futures Lab and a senior fellow for the Defense and Security Department at CSIS.
