Caught between two technological empires, the nations of Southeast Asia are reaching for the same diplomatic instincts that preserved their independence during the Cold War — hedging, balancing, and refusing full alignment. But artificial intelligence is not geopolitics alone; it is capital, compute, and code, and the old tools of neutrality may not be sufficient for a domain where scale determines sovereignty. The region's governments are building local AI models and frameworks, yet remain structurally dependent on the very ecosystems they seek to escape, raising a deeper question: whether au
Southeast Asia's AI Hedging: Can Regional Powers Escape US-China Competition?
Managed interdependence, not independence
Mark
So Southeast Asia is basically trying to play both sides in the AI race, the way they did during the Cold War?
Mimi
That's the instinct, yes. Vietnam, Singapore, the others—they're all trying to develop their own AI capabilities while staying connected to both the US and China. But it's much harder now because AI requires massive compute power and data that individual countries can't easily build alone.
Luke
Wait, let's be precise about what's actually happening. Vietnam has built some localized language models, but they're using Nvidia chips from the US and getting help from Chinese and American firms. That's not independence—that's adaptation.
Mimi
Right, and that's the point. They're not trying to build everything from scratch. They're trying to reduce dependency by creating local versions of global models.
Mark
But can that actually work? Can you really have sovereignty over AI if you're dependent on foreign chips and software?
Luke
The sources say no, not really. Taylor and Tan are pretty clear: individual countries can't match US or Chinese scale. So what Vietnam and Singapore are doing is more like... managed borrowing.
Mimi
Which is why the real argument in the piece is for regional cooperation instead. If Southeast Asian countries worked together—like Airbus did in Europe—they might actually build something that could compete.
Mark
How would that even work? Would governments have to give up some control?
Mimi
Yes. They'd need aligned policies, shared investment in chips and cloud infrastructure, maybe even joint AI models. It would require countries to coordinate in ways they haven't before.
Luke
And there's no guarantee it would work. Airbus succeeded because Europe had the wealth and political will. Southeast Asia is more fragmented, and the US and China have already invested heavily in the region.
Mark
So the hedging strategy—is it actually buying them time, or is it just delaying the inevitable?
Mimi
It's buying time and creating some real local capacity. But without regional coordination, individual hedging probably just means they'll end up dependent anyway, just on different terms.
Der Puls
- The United States and China are actively competing to make their AI ecosystems the default infrastructure for Southeast Asia, leaving little room for passive neutrality.
- Vietnam, Singapore, Malaysia, Indonesia, and Thailand are each racing to build localized AI models and sovereign data frameworks before dependency quietly hardens into permanence.
- Beneath the progress lies a structural contradiction — most 'independent' regional AI development still runs on American chips or Chinese software, making true sovereignty more aspiration than reality.
- Researchers warn that no single Southeast Asian nation can match the compute power, talent, or data scale of US or Chinese AI ecosystems, exposing individual hedging strategies as insufficient.
- A regional consortium modeled on Airbus — pooling national governments and private firms into shared AI infrastructure — is emerging as the most credible path toward collective technological leverage.
- Whether ASEAN can summon the political will to align policies, share investment, and cooperate across borders remains the defining uncertainty standing between the region and a genuine third way.
Caught between two technological empires, the nations of Southeast Asia are reaching for the same diplomatic instincts that preserved their independence during the Cold War — hedging, balancing, and refusing full alignment. But artificial intelligence is not geopolitics alone; it is capital, compute, and code, and the old tools of neutrality may not be sufficient for a domain where scale determines sovereignty. The region's governments are building local AI models and frameworks, yet remain structurally dependent on the very ecosystems they seek to escape, raising a deeper question: whether autonomy in the age of AI is achievable alone, or only together.
Southeast Asia finds itself navigating a familiar tension: two superpowers pulling in opposite directions, and a region determined not to be absorbed by either. The United States is promoting its AI technology stack as a global standard, backed by export programs and talk of an AI Marshall Plan. China is building its own capabilities and reshaping international norms. For Southeast Asian governments, the choice between these two ecosystems carries consequences that will outlast any single administration.
Vietnam has moved most decisively toward a third path. Hanoi introduced the region's first comprehensive AI law and a Law on the Digital Technology Industry, treating digital infrastructure as a strategic asset. The state-linked firm FPT runs AI compute on American Nvidia chips but deploys through its own sovereign cloud, while Vietnamese developers have built PhoGPT — a large language model trained on local language data. The strategy is managed interdependence: borrowing foreign technology while cultivating the local capacity to adapt and redirect it.
Singapore, Malaysia, Indonesia, and Thailand are following comparable approaches — launching governance frameworks, developing regionally attuned models like SEA-LION, and carefully balancing US and Chinese investment without fully committing to either. The progress is genuine, but researchers Jacob Taylor and Joshua Tan identify a hard ceiling: individual nations in the region cannot replicate the compute scale, talent depth, or data quality that American and Chinese ecosystems command. What often passes for sovereign AI development is, in practice, localization — domestically flavored platforms built on foreign foundations.
This is where the Cold War analogy both illuminates and falls short. During that era, Southeast Asian nations achieved strategic autonomy not alone but collectively, through coordinated hedging across multiple states. The same logic now points toward a regional solution: a public-private consortium — an Airbus for ASEAN AI — that pools national governments and regional firms into shared chip capacity, cloud infrastructure, and model development. It would demand policy alignment, sustained joint investment, and a willingness to cooperate where competition currently reigns. Without it, the region risks becoming not a third force in global AI but a fragmented market, divided and more easily absorbed by the very powers it sought to balance.
Southeast Asia is caught between two technological superpowers, and the region's governments are reaching for a familiar playbook: the hedging strategies that kept them diplomatically independent during the Cold War. The question now is whether those old tools can work in a domain as complex and capital-intensive as artificial intelligence.
The competition is real and visible. The United States is pushing its AI technology stack—hardware, software, data systems, models—as the global standard, backed by initiatives like the American AI Exports Program and talk of an AI Marshall Plan modeled on postwar Europe. China, meanwhile, is building domestic AI capabilities and working to reshape international standards in its favor. Neither power is content to let Southeast Asia remain neutral ground. For countries in the region, the stakes are high: become dependent on one technological ecosystem or the other, or find a third way.
Vietnam has moved furthest toward that third path. In recent years, Hanoi introduced Southeast Asia's first comprehensive AI law and a Law on the Digital Technology Industry, both designed to assert control over domestic systems by treating digital infrastructure as a strategic asset requiring localized data. The approach is pragmatic rather than purist. The state-linked firm FPT uses American Nvidia chips to power its AI Factory compute capacity, then deploys models through its own sovereign cloud platform. Meanwhile, Vietnamese companies have built PhoGPT, a large language model trained on Vietnamese language data and developed by VinAI and Semikong with FPT's help. The strategy is not independence but managed interdependence—borrowing foreign technology while building local capacity to adapt it, reducing the risk of total reliance on foreign models.
Singapore and other regional powers are following similar paths. Singapore launched an updated AI governance framework in January and developed SEA-LION, an open multimodal model designed to represent Southeast Asian languages and cultures in frontier AI systems. Malaysia, Indonesia, and Thailand are all hedging between US and Chinese investments, trying to maintain options rather than commit fully to either. These efforts show real progress toward greater technological autonomy.
But the progress has limits. Researchers Jacob Taylor and Joshua Tan have noted a hard truth: individual Southeast Asian nations cannot match the scale of compute power, talent pools, or high-quality data that US and Chinese AI ecosystems command. What looks like independent development is often localization—adapting existing American or Chinese models with technology transfers from those same firms, creating domestically flavored platforms rather than domestically controlled stacks. True AI sovereignty remains out of reach for any single country in the region.
This is where the Cold War analogy breaks down and points toward a different solution. During the actual Cold War, Southeast Asian nations secured strategic autonomy not through individual alignment but through collective hedging—multiple states working together to maintain leverage. The same logic could apply now. Rather than each country pursuing its own AI stack, the region could pursue collaborative development through public-private consortiums, with national governments and regional firms building shared capabilities. The model exists: Airbus, the European aircraft manufacturer, was built as a multinational public-private venture that allowed smaller economies to compete in a domain otherwise dominated by giants.
An "Airbus for ASEAN AI" would require uncomfortable choices. Governments would need to align policies across borders, maintain consistent regulatory and infrastructure standards, and commit to joint investment in regional chip and cloud capacity. Private companies would need to cooperate rather than compete. But the alternative—individual nations trying to hedge alone—appears to be a slower path to the same dependency. Without regional coordination, Southeast Asia risks becoming not a third force in AI development but a fragmented market where US and Chinese firms compete for influence over divided, weaker customers. The region has the diplomatic experience to pull off collective hedging. Whether it has the political will is still an open question.
Bemerkenswerte Zitate
National efforts are simply no match for the scale of compute, talent or high-quality data of US or Chinese AI ecosystems— Jacob Taylor and Joshua Tan
Southeast Asian nations are extending their Cold War-era political hedging strategies into the AI development race, seeking to balance between two great powers and develop a third pathway independent of either— Analysis in the piece
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