In the global artificial intelligence (AI) race, the competitive landscape between Washington and Beijing is undergoing a paradigm shift. While the focus was previously on dominating semiconductor chips, data, and computing power, strategic value now lies in human resources: the researchers, engineers, and entrepreneurs driving innovation behind the scenes.
Will Wang, founder of the Shenzhen-based smart glasses company Even Realities, exemplifies this shift. After pursuing a career in Silicon Valley, he chose to return to China not for ideological reasons, but because of its more mature hardware manufacturing ecosystem. For him, future AI innovation requires integrating high-level software design capabilities with reliable, robust hardware production.
However, the mobility of talent that once flowed freely now faces serious challenges. Increasingly protective government policies on technology transfer and investment in both countries have created new boundaries. Li Yaqi, an AI governance expert at the S. Rajaratnam School of International Studies (RSIS), describes this phenomenon as a transition from 'talent circulation' to rigid segmentation.
For top-tier talent, deciding where to work is now influenced by three key factors: compensation, access to computing power, and research freedom. The United States maintains an advantage in frontier AI model research and funding. On the other hand, China offers a vast market and strong industrial integration for those looking to commercialize AI applications into real products.
The long-term risk of this fragmentation is not merely a loss of technical skills on one side, but the disruption of the exchange of 'tacit knowledge.' Informal experience, management culture, and research intuition—which have long served as bridges of understanding between nations—are now at risk of being lost, potentially causing both countries to grow more slowly within their respective isolated narratives.
