When global leaders land in New Delhi this February for the India AI Impact Summit—the next major global convening on AI policy—many will arrive with the same question for the United States: where do we fit in America’s vision of the AI future?
Foreign governments will want to know how their domestic industries can plug into U.S.-led AI initiatives like the AI Exports Program and whether their chips, models, or applications will be included in a U.S.-curated AI stack. The U.S. government has been actively working through this same issue in its own deliberations, as reflected in Commerce Department questions about the role of foreign firms in AI export efforts. These deliberations have inadvertently created the impression of a zero-sum tradeoff: that the United States must choose between a purely domestic, “trusted” stack or a globalized one that introduces foreign dependencies.
However, framing the AI stack as a choice between total exclusion or total openness misreads both the market and the technology. In practice, U.S. companies already operate in a hybrid reality. They collaborate with domestic partners to improve performance, expand reach, or fill capability gaps. They simultaneously partner with foreign firms whenever those collaborations enhance competitiveness, accelerate technical progress, or support global deployment. AI implementations almost always involve a combination of domestic and international components.
Both forms of collaboration are central to AI diffusion, and U.S. policymakers should make clear they are focused on extending the reach of both: strengthening domestic collaboration where American firms can scale together, and amplifying foreign partnerships when they broaden American AI diffusion or advance strategic goals in third markets.
That means U.S. policymakers should be advocating on the global stage that countries interested in working with the United States are welcomed as partners across the AI lifecycle, including joint development financing, coordinated deployments, and co-supported capacity-building initiatives. Framed properly, these mechanisms do not dilute U.S. influence. They extend it by embedding U.S. technology in broader delivery networks, leveraging partners’ capital and institutional reach, and accelerating diffusion into markets the United States cannot effectively reach on its own.
A practical example shows why this matters. NVIDIA and Mistral have partnered to produce highly efficient open-weight models—a collaboration driven by technical logic but with clear geopolitical relevance, given China’s aggressive push of its own open-source models in emerging markets. The United States could work with France to champion this joint offering in contested regions where China is gaining influence.
In many parts of the world, diplomatic and development channels also run more deeply through non-U.S. actors. In Southern Africa, the UK–Canada–Sweden-funded Artificial Intelligence for Development (AI4D) program plays a central role in supporting local AI ecosystems, while in East Africa, it is the German-funded Digital for Development (D4D) initiative. Leveraging those allied networks alongside U.S. technology would extend diffusion farther and faster than Washington could achieve alone.
What the United States communicates in New Delhi about the role of allies in its AI strategy will shape how far, how fast, and how durably U.S. technology spreads. Making clear that partners have a place in building, deploying, and scaling AI is not a concession. It is how American AI goes further and moves faster.
