The new "American AI Exports Program" and "Tech Corps" initiative mirror the strategy used to compete with Huawei's 5G dominance. By offering attractive financing and on-the-ground training, the US aims to provide developing nations a complete solution to build AI capabilities with American technology.
The US focus on exporting hardware (chips, data centers) over proprietary models suggests a strategic belief that open-source AI will eventually dominate. If models become a free commodity, the most valuable and defensible part of the AI stack becomes the underlying compute infrastructure.
The White House's Michael Kratsios reframes "AI sovereignty" as owning American-built hardware and infrastructure, not renting access to US cloud models. This strategy encourages partner nations to buy the AI stack ("They build it. It's yours.") rather than remaining dependent on subscriptions.
The competition in AI infrastructure is framed as a binary, geopolitical choice. The future will be dominated by either a US-led AI stack or a Chinese one. This perspective positions edge infrastructure companies as critical players in national security and technological dominance.
The decision to allow NVIDIA to sell powerful AI chips to China has a counterintuitive goal. The administration believes that by supplying China, it can "take the air out" of the country's own efforts to build a self-sufficient AI chip ecosystem, thereby hindering domestic firms like Huawei.
Counterintuitively, China leads in open-source AI models as a deliberate strategy. This approach allows them to attract global developer talent to accelerate their progress. It also serves to commoditize software, which complements their national strength in hardware manufacturing, a classic competitive tactic.
Restricting sales to China is a catastrophic mistake that creates a protected, trillion-dollar market for domestic rivals like Huawei. This funds their R&D and global expansion with monopoly profits. To win the long-term AI race, American tech must be allowed to compete everywhere.
Selling semiconductor equipment allows China to create hundreds of billions in downstream value. In contrast, selling API access to US models is a higher-margin strategy that keeps core value creation within the American ecosystem, extracting more revenue per unit of capability provided.
Restricting allies like the UAE from buying U.S. AI chips is a counterproductive policy. It doesn't deny them access to AI; it pushes them to purchase Chinese alternatives like Huawei. This strategy inadvertently builds up China's market share and creates a global technology ecosystem centered around a key U.S. competitor.
The AI competition is not a simple two-horse race between the US and China. It's a complex 2x2 matrix: US vs. China and Open Source vs. Closed Source. China is aggressively pursuing an open-source strategy, creating a new competitive dynamic that complicates the landscape and challenges the dominance of proprietary US labs.
Framing the US-China AI dynamic as a zero-sum race is inaccurate. The reality is a complex 'coopetition' where both sides compete, cooperate on research, and actively co-opt each other's open-weight models to accelerate their own development, creating deep interdependencies.