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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesAt a May 8, 2025, Senate hearing, Microsoft’s Brad Smith argued that the United States cannot secure AI leadership by inventing advanced systems alone: it also has to spread them through infrastructure, applications, talent and international markets. That was not a concession that America could not lead, or a call to give every country unrestricted access. It was an argument for a globally connected, U.S.-led AI ecosystem—one that also aligned with the commercial interests of the companies making the case.
What happened at the Senate hearing
The Senate Committee on Commerce, Science, and Transportation held “Winning the AI Race: Strengthening U.S. Capabilities in Computing and Innovation” on Thursday, May 8, 2025. Chair Ted Cruz, a Texas Republican, and ranking member Maria Cantwell, a Washington Democrat, heard testimony from OpenAI CEO Sam Altman, Microsoft Vice Chair and President Brad Smith, AMD CEO Lisa Su, and CoreWeave CEO Michael Intrator. The committee framed the hearing around the infrastructure and capabilities the United States would need to compete with China. The committee’s announcement lists the witnesses and hearing purpose.
The mix of witnesses reflected a broad view of the AI supply chain: data-center infrastructure, chips, cloud and model platforms, and applications that put AI into use. The argument was not only about which company could build the most capable model. It was also about whether the United States could build, power and deploy AI at scale.
What “no one country can win AI” meant
The headline phrase is a compressed description of Smith’s argument, not necessarily a joint verbatim statement from OpenAI and Microsoft. In his written testimony, Smith distinguished innovation—creating new AI capabilities—from diffusion—putting those capabilities into use across businesses, governments, developers and markets. He argued that both matter to competition. Smith’s testimony sets out that case.
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In this framing, U.S. leadership does not require the United States to control every model, chip, data center or national AI ecosystem. It requires American companies and institutions to build influential systems and see them widely adopted. International deployment can extend the reach of U.S. platforms, technical standards and applications; it is therefore part of the strategic contest, not a retreat from it.
That still leaves an important boundary question: which technologies and forms of access should be shared, and which should be restricted for security reasons? The testimony’s emphasis on diffusion did not settle that question or amount to support for unrestricted transfers.
Why energy and infrastructure were central
AI capacity depends on more than software. The witnesses’ case linked data centers and advanced accelerators to electricity generation, grid connections, cooling, construction and skilled labor. If power projects or data centers cannot be built and connected, hardware and models cannot be deployed at the scale companies seek. Altman described the next phase as requiring both “abundant intelligence” and “abundant energy,” according to VentureBeat’s contemporaneous account of the hearing.
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The policy implication was faster permitting and more capacity for power and computing. But faster approvals are not an answer by themselves: communities and governments still face choices about water use, electricity costs, land, pollution, grid reliability and local oversight. The hearing’s call to remove infrastructure bottlenecks did not resolve how to balance those interests.
Microsoft’s case: succeed at every layer and reach global markets
Smith described an “AI tech stack” extending from infrastructure and hardware through foundation models and platforms to applications and users. His point was that U.S. leadership would depend on the strength of the whole chain, not on a single model or company. Microsoft also connected overseas infrastructure and deployment to American influence. In its publication of Smith’s testimony, the company said it was building AI infrastructure in more than 40 countries; that is Microsoft’s own figure, not an independent measure of global market reach. Microsoft’s publication provides its account of the testimony.
The policy priorities implicit in that case included quicker data-center approvals, more generation and grid investment, a larger technical workforce, immigration pathways for AI and software talent, and overseas access for U.S. systems. Smith’s position also tied export rules to commercial relationships: if rules make U.S. technology difficult to obtain in countries that are not adversaries, those markets may look elsewhere. That concern does not mean every destination or capability should receive the same access.
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OpenAI’s case: infrastructure partnerships and international reach
Altman’s written testimony linked AI to national power, infrastructure investment, safety as capabilities grow and the influence of democratic systems. It also described OpenAI for Countries, a proposed partnership model through which countries could develop domestic AI infrastructure and ecosystems while investing in the Stargate project and broader U.S.-led capacity. This was a proposal in testimony, not an enacted government program. Altman’s written testimony describes the plan.
OpenAI’s position combined several aims: U.S. strategic leadership, wider international deployment, partnerships around infrastructure, and safety language. Calling it simply “global cooperation” would miss the commercial and geopolitical dimensions. International partnerships could expand AI capacity and adoption while also creating markets for U.S. companies and strengthening a U.S.-aligned technology ecosystem.
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What the senators agreed on—and where they differed
Both party leaders treated AI leadership and competition with China as important. Their emphasis differed, particularly over regulation and the role of government.
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Cruz and the Republican case for speed
Cruz argued that the United States should compete through faster innovation rather than adopting what he characterized as Europe’s more restrictive approach. He said he planned to pursue an AI regulatory sandbox modeled in part on the early U.S. internet policy environment. Cruz’s statement sets out that argument.
Cantwell and the case for adoption, exports and public investment
Cantwell also emphasized U.S. leadership, but stressed foreign adoption of American AI, computing power, algorithms, high-quality data, semiconductor supply chains, and public-private research and investment. She described an open, U.S.-led architecture as an alternative to a closed system. Here, “open” is a strategic and market concept; it should not be read automatically as a call for fully open-source frontier models. Cantwell’s statement explains her priorities.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Regulation: targeted safeguards, not no rules
The industry position described in hearing coverage was that regulation should not unnecessarily delay deployment, require government pre-approval for every model release, fragment the U.S. market with conflicting state rules, or leave American products less competitive overseas. But the witnesses’ position was not simply that AI should have no rules: they supported standards and safety measures in some areas while opposing broad pre-approval regimes they believed would slow development or diffusion. VentureBeat’s account reports that distinction.
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These claims are policy arguments from companies with a direct interest in faster commercialization. Whether a particular rule is an unnecessary barrier or a useful safeguard depends on what it covers, how it is enforced and what risks it addresses. The hearing did not settle those questions.
Why global access and export controls are in tension
Diffusion creates a strategic dilemma. Wider overseas use of U.S. AI can bring revenue to American firms, increase reliance on their platforms and help establish U.S. standards. But advanced chips, computing capacity, model access and technology transfers can also raise national-security risks, including dual-use applications. The aim of broader reach can therefore conflict with the aim of restricting sensitive capabilities.
Those are related but distinct policy choices: exporting chips is not the same as exporting models or cloud services; building infrastructure abroad is not the same as allowing foreign access to advanced computing. VentureBeat reported that Smith objected to quantitative caps affecting “tier two” countries, arguing that such limits sent a negative signal to nations seeking U.S. AI access. That reported objection is not evidence that he opposed every export control.
The commercial interests behind the testimony
The witnesses offered strategic arguments, but they also spoke for businesses that could benefit from the policies under discussion. More data centers and AI computing could mean more demand for cloud services, chips and model capacity; easier permitting, access to skilled workers and international deployment could support expansion. The interests differ by company:
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- Microsoft: Greater cloud infrastructure use and enterprise adoption could reinforce its Azure and AI businesses, while wider international deployment could extend its distribution.
- AMD: Expanded demand for AI accelerators and a more diversified hardware market could benefit its semiconductor business.
- CoreWeave: More demand for GPU cloud capacity and AI data centers could benefit its specialized infrastructure business.
Those incentives do not by themselves disprove the witnesses’ national-security arguments. They do mean the requested policies should be understood as both strategic recommendations and industry advocacy, rather than as disinterested assessments of what the country must do.
What the phrase means—and what it does not
- It means: Smith argued that U.S. leadership depends on global reach, international relationships, talent and widespread adoption as well as invention.
- It does not mean: The United States cannot lead, that all countries should get identical access to frontier AI, that export controls should disappear, or that the companies rejected national-security competition.
The unresolved policy question beneath the headline is how the United States can widen the international deployment of its AI systems while protecting sensitive technology and maintaining public oversight at home. The hearing put that tension on display; it did not resolve it.
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