China is banking on artificial intelligence (AI) to become a new growth engine, with projections suggesting it could add several trillion yuan to the economy by 2035 amid a sweeping national push for computing power and a unified data market.
At the China Computing Power Conference held in Datong, Shanxi province, over the weekend, Beijing showcased the depth of this ambition. Officials announced that 10 provinces and municipalities – ranging from Shanghai and Zhejiang in the east to Qinghai and Xinjiang in the west – had joined a unified computing platform designed to match surging business demand with underused resources across regions.
The initiative marks a critical step in knitting together China’s patchwork of regional computing hubs into a seamless national grid. State broadcaster CCTV reported that the platform had already onboarded more than 100 service providers, 1,000 industry users, and nearly 100 AI models, underscoring the speed at which Beijing is mobilizing both state and private sectors to build capacity.
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This drive comes after years of heavy investment in data centers and semiconductor development as part of China’s self-reliance campaign, particularly amid escalating technology tensions with the United States. Over the past five years, China’s overall computing capacity has expanded by about 30 percent annually. This expansion is set to accelerate: smart computing power, tailored for AI applications, is projected to grow by 43 percent this year alone, according to an AI-computing-power assessment by the International Data Corporation and Inspur Information.
The International Data Corporation also projected that between 2023 and 2028, China’s smart computing power would grow at a compound annual rate of 46.2 percent—far outpacing the 18.8 percent growth expected for general-purpose computing.
Rao Shaoyang of the China Telecom Research Institute framed the potential scale of this transformation, stating that AI could contribute more than 11 trillion yuan (about $1.5 trillion) to China’s GDP by 2035. If realized, this would cement AI as one of the country’s primary engines of economic growth.
This effort mirrors a similar push in the United States, where Washington has made AI infrastructure central to future competitiveness. The Biden administration supported federal funding for advanced chips, new data centers, and AI research hubs through initiatives tied to the CHIPS and Science Act. The U.S. is also building a more distributed AI ecosystem, with national labs, major universities, and cloud providers expanding computing clusters to serve researchers and private companies.
President Donald Trump, in January, announced Stargate, a $500 billion AI investment initiative aimed at cementing America’s leadership in artificial intelligence. But unlike China’s centrally coordinated approach, the U.S. model relies on partnerships between government, academia, and industry, with companies like Nvidia, Microsoft, SoftBank, and Google Cloud playing an outsized role in supplying computing resources.
The parallel efforts underscore how the world’s two largest economies are racing to make AI the backbone of future growth. While China is banking on a state-led, unified data and computing system to supercharge its AI economy, the U.S. is banking on a mix of private sector innovation and government-backed infrastructure. Both see AI not just as a technological frontier but as an economic pillar that could define global leadership in the decades ahead.
Against this backdrop, China hopes to reduce inefficiencies, cut reliance on foreign technology, and build a data infrastructure that can support industries from finance to healthcare and advanced manufacturing by weaving together its computing resources.
Beijing’s approach contrasts sharply with Western markets, where computing resources are often fragmented across competing private providers. China is betting that scale and coordination will give its industries an edge in the global race for AI dominance by building a centralized, state-backed platform.
The broader strategy reflects a recognition that AI leadership will depend as much on raw computing power and data as on algorithms. As the U.S. continues to tighten restrictions on high-end chips and cloud services available to Chinese firms, Beijing’s response has been to accelerate its domestic capabilities.
With the unified computing power network already attracting a critical mass of users and models, analysts say the challenge ahead will be ensuring interoperability, maintaining security across provinces, and driving adoption in traditional industries.