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The global AI race is being shaped by two distinct innovation ecosystems. While headlines fixate on which country has the most capable frontier model, the more consequential contest is which ecosystem deploys AI most effectively across the real economy. The US leads in frontier foundation models, funded largely by private capital; China's edge lies in the structural inputs backed by the state that decide deployment at scale—engineering talent, low-cost renewable power and manufacturing, and vast real-world data. This closed-door roundtable convenes leading investors to shed light on the differences between the two systems: Where is each ahead? How is open-source challenging the economics of proprietary models? How will chip access and export controls reshape the race? If AI leadership is ultimately decided by productivity gains rather than benchmark scores, which system is better positioned, and what does that mean when deciding where to deploy capital?