ASEAN Nations Navigate Pressure to Align with Either US or Chinese AI Ecosystems

The Balancing Act Grows Harder

Southeast Asia's technology sector has long thrived on pragmatism, drawing investment, cloud infrastructure, and research partnerships from both American and Chinese firms without declaring exclusive allegiance to either. That flexibility is now under strain. As Washington and Beijing each assemble distinct artificial intelligence ecosystems, complete with their own chip supply chains, model architectures, and governance frameworks, governments and enterprises across ASEAN find themselves fielding increasingly pointed questions about which sphere they intend to join.

At Opentechwire, we've tracked more than a dozen bilateral AI agreements signed between ASEAN member states and either the United States or China over the past eighteen months. What stands out is not the volume but the tenor: these are no longer simple memoranda of understanding on research collaboration. They involve commitments on data residency, procurement of training hardware, and adoption of specific safety and auditing standards. Each agreement nudges a country a step closer to one bloc or the other, even when the signatories insist otherwise in public remarks.

The shift reflects a broader reality. Artificial intelligence infrastructure is not neutral. The silicon that powers training runs, the datasets that shape foundation models, the regulatory templates that define acceptable use are all deeply embedded in national strategic priorities. When a Southeast Asian government selects an American hyperscaler to host its national AI platform, it implicitly accepts a technology stack subject to US export controls and compliance regimes. When it partners with a Chinese AI lab, it may gain access to models optimised for multilingual Asian contexts but must navigate Beijing's own data sovereignty expectations.

What Each Side Offers

The American value proposition centres on access to cutting-edge chips and the most capable large language models. NVIDIA's H-series accelerators remain the gold standard for training at scale, and US-headquartered labs continue to lead in benchmark performance across reasoning, multimodal understanding, and long-context tasks. For ASEAN countries seeking to build sovereign AI capabilities, partnerships with American firms promise state-of-the-art tooling and integration into a research network that spans Stanford, MIT, and the major corporate labs.

Yet that access comes with strings. US export controls on advanced semiconductors, tightened repeatedly since 2022, mean that certain chip architectures cannot be sold to countries deemed insufficiently aligned with Washington's technology security agenda. Even friendly nations have found themselves subject to licensing delays or outright refusals when procurement requests touch sensitive performance thresholds. For a Thai or Indonesian ministry planning a multi-year AI rollout, that uncertainty is a liability.

China's pitch is different. Chinese firms emphasise interoperability with existing manufacturing and logistics ecosystems that already run deep across Southeast Asia. They offer models trained on datasets that include substantial Chinese, Malay, Thai, and Vietnamese corpora, making them more effective for local-language applications than models tuned primarily on English text. Pricing is often more flexible, and Chinese state-backed investors have shown willingness to co-fund data centre construction and talent development programmes that American venture capital typically avoids.

The trade-off is geopolitical. Accepting Chinese AI infrastructure means navigating Beijing's expectations around data flows and content moderation, particularly for applications that touch sensitive sectors such as finance, telecommunications, or government services. It also risks triggering scrutiny or sanctions from Washington, especially if the partnership involves firms on US entity lists.

The Cost of Choosing

For businesses operating across Southeast Asia, the fracturing of the AI landscape into competing blocs introduces friction that did not exist three years ago. A logistics company that built its route optimisation system on Chinese-developed models may find that system incompatible with the compliance requirements of an American client. A fintech startup that trained its fraud detection engine using infrastructure in Singapore, which maintains close ties with US cloud providers, may struggle to expand into markets where Chinese technology dominates.

Interoperability between the two ecosystems is declining. American and Chinese AI labs increasingly use different tokenisation schemes, different fine-tuning frameworks, and different safety alignment techniques. A model trained in one sphere does not easily transfer to the other. For smaller ASEAN countries with limited domestic AI capacity, this means that a decision made today about which partner to work with can lock in a technology trajectory for a decade.

The pressure is not only technical. Diplomatic signalling matters. When a Southeast Asian head of state attends a high-profile AI summit in San Francisco or Shenzhen, counterparts in the other capital take note. When a national research council signs a joint lab agreement with a Chinese university, American officials ask pointed questions during the next bilateral economic dialogue. The margin for ambiguity is narrowing.

Regional Responses Diverge

Not all ASEAN members are responding the same way. Singapore, with its deep financial and security ties to the United States, has positioned itself as a trusted node in the American AI network while maintaining commercial relationships with Chinese firms in narrower, less sensitive domains. The city-state's regulators have adopted governance frameworks that closely mirror US and European approaches, a choice that reassures American partners but limits the appeal of Singapore as a hub for Chinese AI companies seeking regional footholds.

Vietnam and Thailand, by contrast, have tried to preserve maximum flexibility. Both countries have signed AI cooperation agreements with Washington and Beijing, and both host data centres operated by American, Chinese, and local firms. Yet even this hedging strategy is becoming harder to sustain. As the two blocs mature, neutrality starts to look less like pragmatism and more like indecision, and both Washington and Beijing are less tolerant of fence-sitting than they were five years ago.

Indonesia and the Philippines face their own distinct pressures. Indonesia's large domestic market gives it leverage to demand technology transfer and local partnerships as a condition of market access, but the country's infrastructure gaps mean it remains reliant on foreign providers for core AI capabilities. The Philippines, meanwhile, has seen its security relationship with the United States deepen in recent years, and that alignment is beginning to shape its technology procurement decisions in ways that were less explicit a decade ago.

The Limits of Non-Alignment

At a policy level, ASEAN has repeatedly affirmed its commitment to centrality and non-alignment in great-power competition. The bloc's official statements on digital governance emphasise openness, interoperability, and the avoidance of technology blocs. In practice, those principles are difficult to operationalise when the underlying infrastructure is fragmenting.

No multilateral framework currently exists that would allow ASEAN countries to access both American and Chinese AI ecosystems without friction. The OECD AI Principles and the Global Partnership on AI, both heavily influenced by Western governments, have limited buy-in from Beijing. Chinese-led initiatives such as the Global AI Governance Initiative have not attracted broad participation from US allies. ASEAN's own efforts to articulate a regional AI governance model remain at an early stage and lack the technical depth to serve as a genuine third way.

The result is a patchwork. Individual ministries and state-owned enterprises make procurement decisions based on immediate needs, budget constraints, and the preferences of senior officials, often without a coherent national strategy. The cumulative effect of these choices, however, is to gradually embed each country more deeply into one ecosystem or the other, even when that outcome was never explicitly intended.

What Lies Ahead

The AI rivalry between Washington and Beijing is not going to ease. Both governments view leadership in artificial intelligence as central to economic competitiveness and national security, and both are willing to use export controls, investment screening, and diplomatic pressure to advance their positions. For Southeast Asia, that means the pressure to choose sides will only intensify.

The question is whether ASEAN countries can extract concessions in exchange for alignment, or whether they will find themselves squeezed between two blocs without gaining meaningful influence over either. The region's leverage lies in its market size, its strategic location, and its role as a manufacturing and data hub. But leverage is useful only if it is exercised collectively, and ASEAN's track record on coordinated technology policy is mixed at best.

For now, the balancing act continues. Governments issue carefully worded statements affirming partnerships with both powers. Businesses build redundant systems to hedge against sudden shifts in the geopolitical weather. Researchers collaborate with labs in both the United States and China, aware that the window for such collaboration may be closing. The pragmatism that once defined Southeast Asia's approach to technology is giving way to a more constrained, more transactional, and ultimately more fragile set of arrangements.