China's Data Strategy Could Give It an Edge in AI Race, US Advisory Body Warns

 

China's data strategy and AI technology illustrating its potential advantage in the global artificial intelligence race.

By CoinAINews Staff 

A U.S. congressional advisory body has warned that China's systematic approach to collecting and commercializing data could give it a strategic advantage over the United States in the global artificial intelligence race.

The U.S.-China Economic and Security Review Commission (USCC), an independent panel that advises Congress on national security implications of the U.S.-China relationship, released a report on Tuesday highlighting Beijing's strategy of treating data as a strategic national asset.


The Data Gap That Matters

As major U.S. AI companies increasingly face limits in sourcing additional high-quality training data from the open internet, China is systematically collecting domestic "enterprise, operational and physical-world data that cannot be scraped"—data that is crucial for training AI tools designed for business use, autonomous vehicles and humanoid robots.

"Over the last half decade, China has been able to consolidate data, find ways to label it and refine it, and hoover up new data and make sure it's quickly made available to entities," said Mike Kuiken, the commission's vice chair.

The report identifies China's advanced manufacturing and industrial robotics ecosystems as potential sources of a data advantage. These sectors provide a vast pool of high-quality data for "embodied AI" applications—AI systems that operate in the physical world, such as robots—giving China a potential edge in developing robotics software for both commercial and military uses.


Beijing's Top-Down Data Strategy

China formally designated data as a core "factor of production" in 2020, elevating it alongside land, labor, capital and technology. The country established the National Data Administration in 2023 to oversee nationwide data standardization and classification, with a mandate to build a unified national market for data trading.

The report describes Beijing's approach as the same "top-down" industrial policy that has made China a leader in advanced manufacturing. Rather than leaving the development of a data economy to market forces, China is building infrastructure where participants can exchange data—fostering third-party services like data valuation, analytics and financing.

Chinese firms have already begun listing proprietary datasets on regional data exchanges in cities including Shanghai, Shenzhen and Beijing, while accounting rules allow companies to record qualifying data resources as assets on their balance sheets.


The Risk of Falling Behind

The USCC warned that the United States risks ceding global leadership in setting international data standards to China, which would give Chinese firms a lasting advantage in industries where data is a central pillar of development.

"Standards are difficult to revise once adopted," the report said. "Engaging now would be more effective than seeking to unwind an established standard later."

The report also highlighted risks for U.S. firms operating in China, who increasingly "risk running afoul of China's strict data and cyber governance regimes" as Beijing tightens regulatory oversight of cross-border data transfer.


A Call for U.S. Action

The USCC's top recommendation was straightforward: Congress should consider developing a national data strategy that treats data as an economic asset—similar to what China has already implemented.

"We recommend that U.S. Congress think about a national data strategy and how the U.S. government could treat data as an economic asset as our number one recommendation," Kuiken said.


The Bottom Line

The commission's report underscores a growing concern in Washington: that the AI race is no longer just about chips and computing power, but about who can best harness the vast, messy world of real-world data.

China has been building an institutional framework to collect, standardize and facilitate the commercialization of data across its economy. Whether the U.S. responds with a similar strategy—or leaves it to market forces—could shape the next decade of AI competition.


This article is for informational purposes only and does not constitute investment advice.

 

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