For years, the race for artificial intelligence leadership has been framed as a contest over advanced semiconductors. But the decisive advantage may belong not to the country that manufactures the best chips, but to the one that can deploy the most computing power across its economy. In the AI era, nanometers still matter. Yet increasingly, so do gigawatts.
China’s emerging strategy, including plans to connect AI data centers via a national computing network and expand supporting energy infrastructure, reflects a broader belief that AI leadership will be determined by large-scale deployment. Governments focusing mainly on semiconductor fabrication may be chasing past advantages instead of future ones. China’s reported plan to invest roughly 2 trillion yuan (i.e., $295 billion) over five years in a nationwide network of interconnected AI data centers underscores the scale of this strategic shift.
We can compare the global data center expansion trajectory. For the United States, McKinsey’s latest analysis puts U.S. data-center power capacity at 30-plus GW in 2025, rising to 90-plus GW by 2030. For China, Rystad estimates China’s total data-center capacity will rise from 32 GW at the end of 2025 to more than 60 GW in 2030. AI facilities are expected to increase from 39 percent of capacity in 2026 to 48 percent in 2030, implying roughly 29 GW by 2030. In the same study, it was estimated that global capacity would reach 155 GW, meaning the United States and China combined would account for roughly 77 percent of global AI capacity.
