Dividends not division

The two major countries should work together to address risks posed by AI and ensure the technology is harnessed for the global good

A new round of the artificial intelligence revolution driven by large language models is accelerating at a rapid pace. AI has evolved far beyond a purely technical issue to become a core strategic variable reshaping the global competitive landscape. As a transformative technology spearheading the new scientific and industrial revolution, AI is comprehensively reshaping modes of production and industrial structures. Competition and collaboration centered on AI will help shape the balance of power among major countries in the 21st century.

Over the past two years, major economies have stepped up efforts to formulate top-level national AI strategies, embedding AI in national development blueprints and mobilizing nationwide resources to sustain their competitive edges in this field. In July 2025, the United States released Winning the AI Race: America's AI Action Plan, charting a decisive course to cement US dominance in AI. In November 2025, the US launched the Genesis Mission, described as a historic nationwide initiative comparable in urgency and ambition to the Manhattan Project during World War II. It integrates supercomputing resources, research datasets from several national laboratories and private-sector large-scale model capabilities to build a unified computing platform. In July 2026, the White House published the report Science: A New Golden Age, advocating an overhaul of the US research system.

China and the US are leading the global development of AI. According to core AI indicators in Stanford University's 2026 AI Index Report, China and the US account for the vast majority of global resources and outputs in computing capacity, industrial application and high-impact academic papers — a lead unlikely to be challenged by other nations in the near term. In computing supply, both countries maintain advantages in high-end chip reserves and the scale of computing hubs. An Oxford University study titled AI Compute Sovereignty: Infrastructure Control Across Territories, Cloud Providers and Accelerators, found that major AI computing clusters are concentrated in the two nations: 26 in the US and 22 in China.

Stanford's report also indicates that the US retains an edge in developing top-tier frontier models, yet China is closing the gap rapidly. While the US leads in quantity, Chinese models are catching up fast in quality. The comprehensive performance gap between leading Chinese and US frontier models stands at just 2.7 percent, with models from both sides alternating at the top of rankings since early 2025, marking a phase of parallel technological progress. Regarding supporting factors such as AI talent and data, the US still hosts the world's largest pool of elite AI researchers and retains advantages in attracting top original innovators. According to China's National Development and Reform Commission, China possesses one of the biggest cohorts of AI engineers, producing more than 5 million STEM graduates every year. In 2025, according to the National Data Resource Survey Report (2025) released by China's National Data Administration, China generated 52.26 zettabytes of data, accounting for 27.44 percent of the global total and ranking among the world's largest data resource holders. These scale advantages in talent and data lay a solid foundation for sustained long-term AI growth.

AI is a shared endeavor of humanity, and its sound development bears on the common well-being of all. As the two major forces driving global AI progress, China and the US can transcend zero-sum competition, strengthen their collaboration, jointly address global challenges arising from AI and advance the ethical and beneficial development of AI.

First, China and the US can work together to support AI cooperation between the Global North and the Global South as well as South-South cooperation to build an open and inclusive global AI governance system. Severe imbalances persist in global AI development, with many developing countries facing bottlenecks in computing power, data, talent and technology. Both sides should abandon zero-sum thinking, uphold the principle of extensive consultation, joint contribution and shared benefits, and help developing countries build their AI capacity through technology transfer, capacity building and talent training.

Second, China and the US can jointly guard against AI risks. While rapid AI innovation unlocks enormous opportunities, it also brings risks including algorithmic bias, privacy breaches and ethical conflicts, with potential implications for international security and global stability. Faced with these transboundary risks, China and the US can deepen dialogue and cooperation on AI safety governance, ethical norms and standard-setting, and jointly improve early-warning and response mechanisms to ensure AI evolves along a secure and reliable track.

Finally, the two countries can jointly harness AI to benefit humanity and tackle global challenges. AI offers new tools to address climate change, public health emergencies, food insecurity and energy shortages. The two nations can pursue pragmatic cooperation in AI-enabled low-carbon transition, pharmaceutical research and equitable access to quality education, turning AI into a powerful instrument for resolving shared challenges facing humankind.

History shows that the dividends of technological revolutions can reach all humanity only through positive interaction and responsible leadership among major countries. While pursuing healthy competition, China and the US should deepen practical cooperation to enable AI technologies to serve the well-being of people across the world. This serves the fundamental interests of both countries and meets the shared expectation of the international community.

Shen Yujing is the deputy director of the Macro Research Department at the Chongyang Institute for Financial Studies at Renmin University of China. Dong Jimeng is a research intern at the Chongyang Institute for Financial Studies at Renmin University of China.

The authors contributed this article to China Watch, a think tank powered by China Daily. The views do not necessarily reflect those of China Daily.

Contact the editor at editor@chinawatch.cn.