Strategic Asymmetry in the US-China Artificial Intelligence Competition

1. Introduction:

Two Races, Two Finish Lines

While the United States and China are engaged in a well-documented artificial intelligence competition, they are pursuing fundamentally different strategic objectives. This dynamic creates a strategic asymmetry where both nations are effectively running separate races toward different finish lines.

While the U.S. pursues a moonshot for Artificial General Intelligence (AGI), China is executing a ground-game to embed "embodied AI" across its industrial base—a divergent path that questions the very definition of winning the AI race.

2. A Comparative Analysis:

Strategic Artificial Intelligence Goals

The divergent paths of the United States and China reflect distinct national priorities and economic incentives.

2.1. The United States:

The Quest for Artificial General Intelligence (AGI)

The prevailing U.S. strategic doctrine conceives of the AI competition as a race toward AGI, defined as self-improving artificial intelligence that surpasses human cognitive power.

Within this framework, the measure of success is often viewed as building the "biggest, most beautiful model," a pursuit backed by hundreds of billions of dollars in investment into models, chips, and AI infrastructure.

Incentives within the U.S. market direct AI development toward consumer applications and enterprise software, where the potential for near-term profits is highest.

2.2. China:

Industrial Diffusion and "Embodied AI"

China's strategy is less focused on large frontier models and more on wiring intelligence into the physical economy at scale. President Xi Jinping has framed the nation's AI development as "application-oriented," a vision reflected in policies such as the "city brain" pilots that fuse traffic cameras and IoT sensors with autonomous vehicles.

This approach treats AI as an "input to production rather than a product itself," with a primary focus on the deployment of "embodied AI" within the manufacturing domain to achieve comprehensive industrial transformation.

3. Giants with Resource:

Resource Allocation and Implementation

United States	China
Investment Focus: Wagering on "hundreds of billions of dollars of compute, hyperscale superclusters, and ever-larger language models."	Investment Focus: Focusing on smaller-scale AI applications to power industrial robots and intelligent manufacturing.
Key Metrics: The National Institute for Standards and Technology's (NIST) AI benchmarking report found the best US model outperformed China's DeepSeek V3.1 across almost every benchmark, including by a 20 percent margin in software engineering tasks.	Key Metrics: Operates roughly 2 million industrial robots (a majority now made domestically) and installed about 295,000 in 2024 alone, compared to approximately 34,000 in the US.
National Strategy: Has no formal plan comparable to China's, relying instead on entrepreneurs to develop and deploy new applications across the economy.	National Strategy: The 14th Five-Year Plan calls for "comprehensive intelligent transformation" of industrial production, with targets for AI to be embedded across 70% of key sectors by 2027, 90% by 2030, and 100% by 2035.

4. Global Supply Chain:

Supply Chain Control as a Strategic Amplifier

The strategic asymmetry is amplified by each nation's distinct approach to economic controls. The United States employs a "small yard, high fence" doctrine, concentrating its efforts on restricting China's access to the most advanced GPUs to hinder its progress in the race toward AGI.

In contrast, China has implemented a "big square, great wall" policy, which focuses on consolidating control over the essential inputs for advanced technology.

According to the International Energy Agency and the U.S. Geological Survey, China holds a dominant global market position in the refining of several critical materials essential for advanced chipmaking, sensors, and batteries, including:

Beijing has extended this control with downstream export regulations on rare-earth magnets and the processing know-how required to produce them.

These rules layer new chokepoints atop old ones, transforming not just the raw materials of modern computing but the tools and know-how required to reproduce them into instruments of strategic leverage.

5. Conclusion:

Strategic Implications of a Divergent Competition

The differing AI strategies of the United States and China have profound strategic implications. China's strategy demonstrates a powerful internal coherence: its focus on embedding AI into the physical economy is amplified by its systematic consolidation of control over the physical raw materials required to build advanced hardware globally.

This approach, anchored in manufacturing dominance and resource security, represents a significant and durable challenge to US technological leadership.

U.S. complacency in its software-centric model development represents a significant strategic blind spot. China's dominance over the physical inputs of technology could allow it to make it "vastly harder to build the chips and other advanced technologies of tomorrow," potentially undermining the very foundation of America's AGI-focused strategy.