ZH reported, citing a May 25 report from China Daily.
As artificial intelligence development accelerates in both China and the United States, economists and policy experts are increasingly calling for closer cooperation between the world’s two leading AI powers — particularly in the areas of safety standards and global governance.
While competition between the two countries remains intense, a growing consensus is emerging that AI is advancing too quickly, and at too large a scale, to be managed effectively without some level of coordination.
Two AI Powers, Different Strengths
The United States continues to lead in several foundational areas of artificial intelligence, including frontier model development, large-scale computing infrastructure, and advanced research into general-purpose AI systems.
China, meanwhile, is rapidly narrowing the gap and has developed particular strengths in deploying AI across real-world industries, including manufacturing, logistics, consumer platforms and public services.
Rather than converging on a single development model, the two countries are increasingly reflecting different priorities in how they define AI progress.
Economist and Nobel laureate Michael Spence noted that the performance gap between leading US and Chinese AI systems has become extremely small.
“There are two main players in frontier AI — China and the US,” he said. “There’s almost no measurable difference between them now in terms of performance. Whatever difference there was, China has caught up.”
Performance Gap Has Narrowed to Single Digits
According to Stanford University’s Institute for Human-Centered Artificial Intelligence, top AI models from the US and China have repeatedly traded positions at the top of global performance rankings since early 2025.
As of March 2026, the leading US model held only a narrow advantage of around 2.7 percent, with differences fluctuating but remaining within single-digit margins over the past year.
The data suggests that AI competition between the two countries is no longer defined by clear technological dominance, but rather by continuous iteration and incremental advantage.
Diverging Models of Innovation
Experts say the most important difference between China and the US is not capability, but development philosophy.
According to former IMF deputy managing director Zhu Min, the United States focuses on scaling frontier models, computational power, and foundational breakthroughs — often framed around the pursuit of artificial general intelligence.
“The US focuses on large models, massive computing power and a strong foundational base,” Zhu said. “What it pursues is the development of intelligence itself.”
China, by contrast, emphasizes integrating AI into the real economy.
“When assessing whether AI is good or not, China places greater weight on the benefits it brings to manufacturing, services and daily life,” Zhu said.
This divergence means that while the US pushes the boundaries of model capability, China is accelerating large-scale deployment across industrial and consumer ecosystems.
Deployment Advantage Becomes a Key Factor
Some economists argue that China’s strength lies not only in adoption speed but in system-wide integration.
Spence noted that China’s policy direction — particularly within the framework of its 15th Five-Year Plan (2026–30) — reflects a more coordinated approach to AI diffusion across sectors.
“China has a better set of plans or intentions to ensure AI is deployed across a wide range of the economy,” he said. “We talk a lot about the diffusion challenge, but we are not doing anything.”
This focus on implementation could become a defining competitive advantage as AI shifts from model training to real-world economic transformation.
Rising Risks Make Governance More Urgent
As AI capabilities expand, experts warn that risks are also increasing — not only in economic terms, but also in social stability, security and potential military applications.
Zhu Min emphasized that AI governance is becoming an urgent global priority.
“AI carries significant uncertainty, including risks related to society, the environment and potential military uses,” he said.
He added that establishing safety frameworks and governance “guardrails” is essential, particularly among the two leading AI powers.
Different Governance Approaches
Experts also point to differences in how China and the US approach AI regulation.
The US is generally described as favoring external governance frameworks — building oversight systems that regulate AI development from the outside.
China, in contrast, tends to emphasize embedding safety mechanisms directly into systems during development and deployment stages.
“Both approaches are valid,” Zhu said. “And together they could shape the future of AI governance.”
Despite differences, there is growing recognition that neither country can manage AI risks alone.
Cooperation Still Possible Amid Competition
Although competition remains central to China-US relations in technology, limited cooperation on AI governance is beginning to emerge.
Both sides have acknowledged the importance of dialogue on AI safety and risk management, including discussions on preventing catastrophic misuse and reducing systemic risks.
US-China relations have recently moved toward what some officials describe as “constructive strategic stability,” with AI increasingly seen as one of the few areas where structured engagement remains possible.
A Shared Challenge for the World
As AI systems become more powerful and widely deployed, the implications extend far beyond bilateral competition.
The development of global standards, safety protocols and governance frameworks is becoming a shared challenge for the international community — and especially for the two countries at the center of AI advancement.
Whether through competition or cooperation, China and the United States are now shaping the trajectory of artificial intelligence worldwide.
And as experts increasingly suggest, the most important question may no longer be who leads in AI — but how both powers can help ensure that its development remains safe, stable and beneficial for the global economy.