The US and China are locked in an AI competition that both nations increasingly view as a winner-take-all race, prompting each to deregulate and accelerate development rather than pump the brakes. New analysis from the Oxford China Policy Lab reveals that policymakers in Beijing and Washington have fundamentally accepted this competitive framework, reshaping how each country approaches AI governance and innovation.

How Are the US and China Responding to AI Competition Differently?

The strategic responses differ in important ways. In the United States, the focus has centered on frontier AI development, meaning cutting-edge models and breakthrough capabilities. China, by contrast, is prioritizing AI diffusion, spreading the technology across industries and society more broadly. Yet both countries share a common instinct: reduce barriers to innovation and speed up development cycles.

Chinese international relations scholars now widely agree that the government has "accepted" the competitive race architecture and is actively working to reduce external dependencies on the US. In the AI realm, this likely means reducing regulatory barriers and incentivizing rapid development and diffusion, in what scholars perceive as a direct reaction to US AI race rhetoric, deregulatory drives, and export controls.

What Are the Key Differences in How Each Country Frames the Competition?

The two nations frame their AI strategies through fundamentally different economic and political lenses. China operates within a more state-directed mixed market model, while the US leans toward capitalist approaches. However, the similarities in how business and political elites approach the competition are striking. Both countries view AI advancement as essential to national security and economic dominance, creating what academic experts call a security dilemma, where each nation's defensive measures appear threatening to the other.

This zero-sum framing has real consequences for how policies are designed. Rather than pursuing collaborative safety research or shared standards, both countries are racing ahead independently. One expert from the Oxford China Policy Lab argued that a more prudent approach would involve working with Beijing to establish shared safety research priorities and jointly develop best practices for containing global AI risks.

Steps to Understanding the Geopolitical Stakes of AI Competition

• Recognize the security dilemma: Both the US and China view the other's AI investments as threatening, creating a cycle where defensive measures by one side prompt accelerated responses from the other, similar to Cold War arms races.
• Understand the diffusion versus frontier divide: The US prioritizes breakthrough models and cutting-edge capabilities, while China focuses on spreading AI technology across industries and society, reflecting different strategic priorities and economic structures.
• Track regulatory divergence: Rather than converging on shared AI governance standards, both nations are reducing internal regulatory barriers to accelerate development, moving in opposite directions from international coordination efforts.
• Monitor supply chain weaponization: Export controls on semiconductors and advanced computing chips have become central tools in the competition, with the US restricting access to technology that China needs for AI development.

The stakes extend beyond technology. Chinese workers are increasingly anxious about AI-driven job displacement, complicating the government's efforts to champion AI as a national asset while managing growing discontent. With stalled post-COVID economic recovery, persistent youth unemployment, and wage stagnation, ordinary Chinese workers feel the threat of automation acutely.

Meanwhile, in the United States, AI-hype-generated job loss anxiety is exacerbating existing long work day culture and the centrality of work to life. Both countries have experienced parallel phenomena in recent years, with quiet quitting in the US mirrored by China's "tangping" (lying flat) and "bailan" (letting it rot) trends among younger generations seeking to escape their respective rat races.

The competitive framework also shapes how middle powers navigate the AI landscape. Research examining US-Netherlands negotiations on semiconductor exports to China found that although the Netherlands controls a critical node in the supply chain through ASML, a major lithography equipment manufacturer, the potential to weaponize this position did not significantly influence US decision-making. This highlights the structural difficulties middle powers face when challenging leaders like the US or China through supply chain control.

Experts at the Oxford China Policy Lab are asking deeper questions about whether this zero-sum framing is inevitable. Rather than simplifying the geopolitical moment into a clash of civilizations, researchers are examining what incentives shape each system's differences and similarities, and how current competition impacts the rest of the world. The fundamental question remains: can structures be built that enable people to live better lives in the emerging AI era, or will the race logic dominate policy for years to come ?