Attempting to hoard technology like a state secret is counterproductive for the US. The nation's true competitive advantage has always been its open society, which enables broad participation and bottom-up innovation. Competing effectively, especially in AI, means leaning into this openness, not trying to emulate closed, top-down systems.
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New technologies perceived as job-destroying, like AI, face significant public and regulatory risk. A powerful defense is to make the general public owners of the technology. When people have a financial stake in a technology's success, they are far more likely to defend it than fight against it.
China is pursuing a low-cost, open-source AI model, similar to Android's market strategy. This contrasts with the US's expensive, high-performance "iPhone" approach. This accessibility and cost-effectiveness could allow Chinese AI to dominate the global market, especially in developing nations.
The current trend toward closed, proprietary AI systems is a misguided and ultimately ineffective strategy. Ideas and talent circulate regardless of corporate walls. True, defensible innovation is fostered by openness and the rapid exchange of research, not by secrecy.
In its largest user study, OpenAI's research team frames AI not just as a product but as a fundamental utility, stating its belief that "access to AI should be treated as a basic right." This perspective signals a long-term ambition for AI to become as integral to society as electricity or internet access.
The most profound innovations in history, like vaccines, PCs, and air travel, distributed value broadly to society rather than being captured by a few corporations. AI could follow this pattern, benefiting the public more than a handful of tech giants, especially with geopolitical pressures forcing commoditization.
The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.
The choice between open and closed-source AI is not just technical but strategic. For startups, feeding proprietary data to a closed-source provider like OpenAI, which competes across many verticals, creates long-term risk. Open-source models offer "strategic autonomy" and prevent dependency on a potential future rival.
A common misconception is that Chinese AI is fully open-source. The reality is they are often "open-weight," meaning training parameters (weights) are shared, but the underlying code and proprietary datasets are not. This provides a competitive advantage by enabling adoption while maintaining some control.
For the first time, a disruptive technology's most advanced capabilities are available to the public from day one via consumer apps. An individual with a smartphone has access to the same state-of-the-art AI as a top VC or Fortune 500 CEO, making it the most democratic technology in history.
Contrary to the belief that distribution is the new moat, the crucial differentiator in AI is talent. Building a truly exceptional AI product is incredibly nuanced and complex, requiring a rare skill set. The scarcity of people who can build off models in an intelligent, tasteful way is the real technological moat, not just access to data or customers.
