The United States is preparing to tell dozens of partner countries that they may have to choose between American and Chinese approaches to artificial intelligence cooperation, but experts warn that Central Asian nations may not be able to afford such a binary choice. According to a draft letter from the U.S. State Department, the issue concerns 35 countries that signed the American AI Opportunity Statement adopted in June. The letter warns that these countries may not be able to participate simultaneously in the U.S.-led Pax Silica initiative and a competing Chinese initiative on artificial intelligence.

What's the Real Difference Between These Two AI Initiatives?

Pax Silica and the World AI Cooperation Organization (WAICO), the Chinese-backed alternative, are not mirror-image organizations, despite how they are often portrayed. Pax Silica is primarily focused on the security and resilience of critical technology supply chains, from minerals and energy to semiconductors, computing infrastructure, and artificial intelligence. WAICO, by contrast, places much greater emphasis on building national capacity, international AI governance, access to technology, workforce development, and greater participation by developing countries in the emerging global AI ecosystem.

The American approach can be broadly described as "Secure the technology ecosystem," while the Chinese approach is more focused on "Expand access to the technology ecosystem." For countries in the Global South, the second approach is particularly attractive because it responds to a genuine demand for training, infrastructure, access to open-weight models (AI systems released publicly without restrictions), and a greater role in shaping international AI rules.

Why Is China Becoming More Competitive in the AI Race?

China is no longer simply catching up with the United States in artificial intelligence. It is competing with the U.S. in performance, cost, and scale of deployment. According to Stanford HAI, in March 2026 the gap between the leading American and Chinese AI models was only 2.7 percent. Since the beginning of 2025, models from the two countries have repeatedly exchanged the lead.

China is strengthening its position through several open-weight models including DeepSeek, Kimi K3, Qwen, GLM, and MiniMax. These models are characterized by rapid development cycles and significantly lower operating costs compared to American alternatives. The U.S. still maintains major advantages in advanced chips, computing infrastructure, capital, and leading AI research laboratories. In 2025, U.S. developers produced 59 notable AI models, compared with 35 in China.

However, China's strategy differs fundamentally. Rather than competing solely on raw capability, Beijing is pursuing a formula of open models, low cost, industrial scale, government support, and rapid deployment. The key question is therefore no longer simply who has the most powerful AI. It is increasingly about who can make advanced AI cheap, accessible, and widely available. That could determine not only technological leadership but also geopolitical influence in the global AI race.

How Can Central Asian Countries Navigate This Pressure?

The foreign policy model of Kazakhstan, Uzbekistan, and other Central Asian countries has traditionally been based on diversification rather than exclusive alignment with a single external partner. Their goal is not so much to balance ideologically between the United States and China as to avoid excessive dependence on any one external power while attracting investment, technology, infrastructure, and access to different markets.

Central Asian countries do not have sufficient resources to build a complete modern AI ecosystem entirely on their own. Building competitive AI infrastructure requires not only skilled professionals but also substantial financial investment, access to advanced technologies, and integration into global technology chains. For most Central Asian countries, building such an ecosystem independently would be extremely expensive and technologically difficult.

The region therefore depends on foreign capital, advanced graphics processing units (GPUs) and computing capacity, cloud platforms, telecommunications equipment, and investment in data centers. International research partnerships, training for engineers and tech specialists, and access to global markets and tech platforms are equally important. The economic cost of cutting cooperation with one of the world's two largest technology centers could therefore be very high.

Steps to Balancing Technology Partnerships in Emerging Economies

• Assess Infrastructure Needs: Central Asian countries must evaluate what specific technology, capital, and expertise gaps exist in their AI ecosystems before committing to any single partnership framework.
• Diversify Technology Sources: Rather than choosing one superpower's approach, nations can selectively adopt components from both ecosystems, such as American security standards alongside Chinese cost-effective infrastructure solutions.
• Negotiate Conditional Participation: Countries can propose participation in both initiatives with explicit safeguards that protect sensitive data and prevent technology transfer restrictions from becoming economic leverage.
• Invest in Regional Capacity: Building shared AI research centers and training programs within Central Asia itself can reduce dependence on external partners for workforce development and innovation.
• Establish Clear Technology Governance: Developing transparent policies about which technologies are adopted for which purposes helps countries maintain strategic autonomy while still benefiting from international cooperation.

The real question for Central Asia is not whether the region can build its own AI ecosystem completely from scratch. The real question is whether it can integrate effectively into the global AI infrastructure while attracting the technology, capital, and expertise it needs. International technology and investment cooperation is not simply an additional advantage. It is a necessary condition for building a competitive AI economy in Central Asia.

It is realistic to expect Washington to become increasingly demanding about where its partners stand on certain sensitive technologies. It is much less realistic, however, to expect Central Asian countries to abandon their multi-vector foreign policies and choose one technology ecosystem at the expense of the other. This distinction is fundamental to understanding how the AI race will actually play out in regions that lack the resources to build independent technological superpowers.