The AI Action Plans: How Similar are the U.S. and Chinese Playbooks?
In July, both the United States and China put forward their national visions for AI development and governance through their own AI Action Plans. Washington’s plan leans into the rhetoric of AI dominance and transactional dealmaking to advance U.S. national interests. In stark contrast, Beijing has pitched the world on a vision of AI governance that opposes U.S. hegemony, supports multilateralism, and embraces global capacity building in its Global AI Governance Action Plan.
Yet beneath the surface, the two countries’ AI strategies are converging in strikingly similar directions. Both now pursue the same three-pronged approach: accelerating domestic AI adoption, enabling government-supported AI exports and the open-source ecosystem, and managing AI risks without constraining development.
This convergence is new. U.S. AI policy has pivoted since President Donald Trump took office, more vocally supporting the open-source ecosystem and AI exports while downplaying AI safety. Chinese AI policy has also transformed, though over a longer time horizon: its AI policy over the last two years has moved away from heavy-handed ideological measures. It now has sufficient technological capabilities to usefully deploy the technology in its economy and globally and has begun to slowly increase its discussion of frontier AI risks in key policy documents.
The AI Action Plans in Context
The two AI Action Plans emerged from markedly different institutional contexts, which shape both their authority and their strategic messaging. The U.S. AI Action Plan, published directly by the White House, carries a more direct connection to the executive branch and represents a continuation of Washington’s “America First” approach to technological leadership. Beijing’s Global AI Action Plan, while issued through the Shanghai World AI Conference, reflects China’s current strategy of positioning itself as a champion of multilateralism and global technological cooperation—a framing that has crystallized in direct opposition to U.S. export controls and unilateral dominance narratives.
A close reading of both plans nevertheless reveals growing U.S.-China convergence in three core aspects of AI policy: accelerating domestic AI adoption, promoting global diffusion and standard setting, and managing AI risks without constraining development.
Domestic Acceleration of AI
Both governments now recognize their global AI ambitions rest not only on their leading AI companies but also on the diffusion of AI throughout many other industries. Both strategies highlight efforts to accelerate AI adoption. Economic diffusion may sound like an obvious goal, but it represents a pivot for both countries, albeit for different reasons.
Much of the Biden administration’s policy was grounded in the belief that scaling the capabilities of frontier AI models was strategically critical. Concrete efforts to drive AI adoption in specific industries, while a priority in the public sector, were less strongly emphasized.
In contrast, China only relatively recently began leveraging AI as a tool for economic growth after several years of imposing tech crackdowns and strict regulatory measures that crippled innovation. During and immediately after the COVID lockdowns, Chinese tech policy focused largely on ensuring that technologies furthered the ideological interests of the Chinese Communist Party. However, the Chinese AI policy has shifted toward an adoption-first strategy that prioritizes broad domestic use in the so-called “real economy.”
According to China’s Global AI Governance Action Plan, that means applying AI into a range of fields such as industrial manufacturing, health care, and agriculture, largely under the banner of “AI Plus”, a Chinese initiative that serves as a rallying cry for AI diffusion in the real economy.
The Race for Global Diffusion and Standard Setting
AI diffusion is a key part of both countries’ economic strategies. Both AI plans confirm that Washington and Beijing see themselves as racing to capture global market share and dominate standard setting—a race they consider increasingly central to their geostrategic ambitions. What’s new here isn’t the race itself, but rather, the two countries’ convergence on a shared urgency and a common set of approaches involving open-source models and government-driven export promotion.
China’s AI action plan is replete with references to openness and open-source AI. Among other things, it calls for “strengthening the open-source ecosystem” by enhancing compatibility, adaptation, and inter-connectivity between upstream and downstream products.
As a companion to its AI action plan, China also recently announced a World AI Cooperation Organization (WAICO) to concretize its ambitions of serving as a key hub of multilateral AI development institutions. Similarly, the U.S. AI Action Plan calls for full-stack AI export packages, reflecting a significant shift from the previous administration, which largely left companies on their own to promote their products.
Muted but Continuing Safety Efforts
Both countries’ AI strategies treat safety as a legitimate concern that is nevertheless clearly less important than economic innovation. This represents an odd kind of convergence—both governments appear to believe AI risks can be managed after achieving competitive advantages, rather than constraining development upfront.
The U.S. AI Action Plan offers the strongest indication that the Trump administration’s vision for AI dominance includes a strong pillar focused on responding to frontier AI risks. Meanwhile, China’s Global AI Action Plan also underscores the importance of AI safety and emphasizes the importance of building out their testing and evaluation ecosystem.
The Path Ahead
The U.S. and Chinese Action Plans outline different approaches in pursuit of similar goals: achieving gains from AI throughout the real economy, pursuing global market share for geostrategic purposes, and mitigating national security risks.
Ultimately, the real determinants lie in how each government turns vision into practice—through budgets, staffing, research and development funds, and infrastructure reforms that shape the pace and scope of adoption. Implementation is likely to look very different across the two systems, with the U.S. relying on a fragmented landscape of federal agencies and private industry, while China depends on the ability of central directives to mobilize provincial governments.
Both Washington and Beijing are pursuing strikingly similar goals, even if they are following different Action Plans. The real winner will not be the country with the better strategic vision, but one that executes theirs best.
