Trump's policies assure China an edge in the race for AI dominance

Mint

19 hours ago

Their tariff war may be facing a stalemate, but the competition for technological supremacy between the US and China is shifting into high gear. As the two countries battle for dominance in artificial intelligence (AI)—with productivity and geopolitical gains expected—one question looms large. Will China's AI capabilities catch up with or even surpass those of the US?
Driving this trend is a series of policies introduced by US President Donald Trump's administration. Trump's presidency marks a dramatic break from the commitment to openness that has underpinned America's technological leadership for decades. Measures intended to bring innovation back to the US may boomerang and end up paving the way for Chinese dominance.
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The evolution of the digital economy may provide some insight into how today's AI race will play out in the wake of Trump's policies. In the 1990s, the US led the internet revolution, dominating the pivotal 'zero to one' phase by quickly moving innovations from lab to market. This fuelled what many lauded as the 'new economy,' characterized by rapid growth, strong productivity gains and low inflation. China, initially a follower, later injected remarkable dynamism into its digital economy by scaling its own innovative technologies.
China's digital development unfolded in three stages. The first was copy-and-follow: from the mid-1990s to the early 2000s, Chinese firms mirrored US models, launching web portals and online services that drove explosive user growth.
The second stage was localization and improvement. As China's digital ecosystem matured between 2005 and 2015, Chinese tech companies began to leverage their deep understanding of domestic users and market conditions to fine-tune their services. Platforms like WeChat and Taobao not only adapted US concepts, but also built on them, eventually surpassing Western counterparts such as WhatsApp and eBay in the Chinese market.
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The third stage has been marked by breakout innovations. Over the past decade, Chinese tech companies have shifted from imitation to innovation, pioneering new digital models and even overtaking foreign competitors. The most strikingly successful example is ByteDance's TikTok, which positioned China at the forefront of online culture, reshaped social media, and forced US firms like Meta to play catch-up.
This dynamic is already evident in fields like renewable energy and electric vehicles (EVs). AI will be no exception. Following the launch of ChatGPT in late 2022, marking AI's transition into its mass-adoption era, China quickly demonstrated its ability to copy Western models.
The release of DeepSeek in January signalled China's entry into the localization and improvement stage, as the company's R1 model was 30-50 times cheaper to use than that of OpenAI. By February, the performance gap between the best Chinese and US models had narrowed to 1.7%, down from 9.3% in 2024. And while it took ChatGPT two months to reach 100 million active users, DeepSeek reached that mark in seven days.
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One of China's key advantages is its deep pool of engineering talent. The country produces four times as many STEM graduates annually as the US. Beyond sheer size, this 'engineer dividend' reflects a strong work ethic and a pragmatic mindset geared toward complex, hands-on optimization, as demonstrated by DeepSeek's system architecture.
With more than 1 billion internet users and a diverse industrial base, China also offers unparalleled conditions for deploying, testing and refining AI applications. China accounts for nearly 30% of global manufacturing output, generating vast amounts of data. In 2019 alone, its manufacturing sector produced 1,812 petabytes of data and we estimate that figure reached 2,435 PB in 2024.
Energy is another critical factor. In 2023, China generated approximately 9,456 terawatt-hours of electricity—32% of the global total and more than double the US output of 4,178 TWh—giving it a major advantage in powering the large-scale data centres essential to widespread AI adoption.
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America's position in the AI race is further undermined by Trump's cuts to research funding and immigration restrictions. In February, 170 employees were laid off, including AI experts, at the National Science Foundation. The agency's budget faces a cut of more than 50%.
These cuts—together with the National Institutes of Health's delayed funding allocations and the freezing of roughly $2.2 billion in federal grants to Harvard University—risk stalling foundational research and impeding AI innovation. Meanwhile, restrictive immigration policies will likely make it harder for the US to attract and retain global talent, potentially triggering a reverse brain drain as skilled Chinese tech workers return home to take up well-paid positions in a growing sector.
While the Trump administration has backed massive infrastructure initiatives like Stargate—a proposed $500 billion AI data centre to be built by OpenAI, Oracle and SoftBank—such projects risk reinforcing Big Tech's dominance and stifling the innovation needed to achieve transformative technological breakthroughs.
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But the deeper issue lies in America's shift away from economic openness. As US companies like OpenAI become increasingly closed, Chinese firms are embracing open-source strategies. And while Trump's trade and immigration policies drive away global talent and international collaborators, China is actively marketing its low-cost AI models to its trade partners.
No doubt, China faces internal challenges, compounded by US trade restrictions that have limited its access to advanced semiconductors. Domestically, Chinese policymakers must strike a delicate balance between encouraging innovation and enforcing strict data controls. But while neither side has an easy path to AI dominance, Trump's MAGA agenda may inadvertently help make China great again. ©2025/Project Syndicate
The authors are, respectively, a senior fellow and deputy director of the Institute of World Economics and Politics at the Chinese Academy of Social Sciences; and a scholar at the National University of Singapore's Lee Kuan Yew School of Public Policy.