In the past two months, China and the United States unveiled AI strategies that differ markedly, shaped by their respective governance models and priorities.
China is pursuing a state-led, centrally coordinated approach aimed at embedding AI across society and driving economic modernization, while the US relies on its private sector to spur innovation and safeguard technological dominance.
The comparison below highlights these divergent strategies, their goals, and their global implications.
A Key Contrast
A central difference between China’s and the US’s AI strategies lies in their fundamental approach and underlying worldview.
China’s Strategy: State-Led and Comprehensive
China’s AI Plus initiative (here and here) is a state-led, top-down strategy that aims for the “extensive and in-depth integration of AI across various fields.”
It sets clear, measurable objectives:
AI adoption in key sectors projected to exceed 70% by 2027
Rising further to 90% by 2030
This reflects a centralized, coordinated effort to embed AI directly into the economy and society. The goal is to cultivate “new quality productive forces”—viewing AI as a tool for economic restructuring and modernization.
China’s commitment emphasizes:
Building foundational capabilities
Promoting a national open-source ecosystem
Leveraging technology for state-directed outcomes
US Strategy: Private Sector-Driven and Focused on Dominance
In contrast, the US strategy—outlined in documents like America’s AI Action Plan (here)—is framed around maintaining US technological primacy and competition with China.
While it also recognizes the need to accelerate innovation and build infrastructure, the US approach focuses on:
Removing regulatory barriers
Empowering the private sector
Preferring open-source AI
Advancing a “full-stack AI export” strategy to allies while restricting access to competitors
The US strategy is explicitly competitive and nationalistic, prioritizing technological dominance and treating AI as a critical component of national security and economic leadership.
Key Differences
Decision Authority
China: Centralized, state-driven, with national targets and top-down implementation
US: Decentralized, market-driven, with government acting as an enabler
Stated Goals
China: Broad-based modernization, using AI as a catalyst for “socialist modernization”
US: Global dominance, “winning the AI race,” framed in security and geopolitical terms
International Engagement
China: Diplomatic and cooperative, with outreach to the Global South
US: Competitive, focusing on strategic alliances while restricting adversaries
Conclusion
Taken together, these measures align closely with each country’s structural conditions and strategic priorities, underscoring their suitability for effective implementation. China and the United States find themselves in a head-to-head contest, with leadership in AI serving as the ultimate prize.
By reflecting their unique economic, social, and institutional characteristics, both strategies enhance policy coherence and the likelihood of sustainable outcomes. This alignment with national priorities not only affirms their appropriateness but also—despite the uncertainties surrounding AI’s short- and long-term impacts—positions them to deliver meaningful results and advance enduring development objectives.
Doug this is such an important topic. From one point of view, open source is an communist activity. The Chinese models are dominating open source AI and that has huge implications for which countries are going to adopt AI. I believe it will be a huge uplift in Chinese soft power given the current political and economic dynamics.