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Two economists from the ASEAN+3 Macroeconomic Research Office are raising alarms about a dollar trap hiding inside the AI boom. And it’s not the one most people are watching.
Chengxu Fu and Xiaguo Huang, writing for AMRO, argue that the real battleground in the AI race isn’t about which country builds the smartest models. It’s about which currency gets baked into AI’s financial plumbing first. Their core point: if AI data centers and infrastructure costs get priced in U.S. dollars, dollar-pegged stablecoins could lock in a new era of American monetary dominance — one that’s harder to dislodge than anything that came before it. The mechanism isn’t force. It’s network effects. And those, once set, are pretty much impossible to reverse cheaply.
Dollar stablecoins are already operational. That’s the key.
Why Stablecoins Win the AI Payment Race
Fu and Huang’s argument rests on a specific kind of payment need that AI creates. As AI systems move into logistics, inventory management, and treasury operations — what they call agentic payments — those systems need programmable, fast, machine-readable settlements. Dollar-pegged stablecoins already offer that. Central bank digital currencies, or CBDCs, don’t. Not yet. Most are still in development or limited pilots, nowhere near ready to handle the volume and speed that AI-driven commerce demands.
So stablecoins get the first-mover slot. And first movers in payment networks tend to stay there. The economists describe a positive feedback loop: more AI activity means more demand for stablecoins, more demand for stablecoins means more dollar liquidity circulating globally, and more dollar liquidity means the whole system tilts further toward U.S. financial infrastructure. Breaking that loop later would be costly and slow.
There’s a secondary effect too. Stablecoins are typically backed by U.S. Treasuries as collateral. So as stablecoin supply grows to meet AI-driven demand, demand for U.S. Treasuries grows with it. It’s basically a built-in buyer for American government debt, emerging from the AI economy itself. That’s not a small thing.
What ASEAN+3 Countries Are Being Told to Do
Fu and Huang direct their warning at a specific group: the thirteen ASEAN+3 nations. That’s Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, Vietnam, China, Japan, and South Korea. These countries, they say, need to move now — before the stablecoin-AI loop becomes self-sustaining and effectively impossible to compete with.
The prescription has two main parts. First, build regional data centers. If AI infrastructure in the region runs on locally owned and locally denominated systems, the dependency on dollar-priced compute gets weaker. Second, develop tokenized money based on local currencies. Not just CBDCs in the traditional sense, but digital, programmable forms of regional currencies that can actually function inside AI-driven financial systems. The goal is to give regional AI commerce a non-dollar payment rail that works — one that lets these countries participate in the AI economy without inadvertently channeling more power toward Washington.
Without those steps, Fu and Huang think the risk is clear: ASEAN+3 nations become consumers of a financial system shaped around U.S. interests, with stablecoin usage as the transmission mechanism. The dollar’s influence in global AI transactions grows, and these countries find themselves with less leverage over their own financial policies than they had before AI scaled up.
It’s a structural concern, not a short-term market call. And it’s probably more urgent than most regional policymakers currently treat it.
The Broader Stakes
What makes the AMRO paper notable is that it frames stablecoin dominance as a geopolitical and macroeconomic issue, not just a fintech one. Stablecoin adoption across Asia has grown sharply in recent years, driven by remittances, cross-border trade, and increasingly, institutional use. The infrastructure for dollar stablecoin use is already spreading. Fu and Huang’s warning is that AI could turbocharge that spread in ways that are qualitatively different — because AI payments aren’t driven by human choice in the same way consumer payments are. When an AI agent picks a payment rail, it picks based on what’s available, programmable, and fast. Right now, that’s dollar stablecoins.
And the feedback loop they describe isn’t hypothetical. It’s kind of already starting. AI companies are pricing compute in dollars. Stablecoin volumes are rising. Treasury demand from stablecoin issuers is real and growing.
The economists aren’t saying dollar dominance through stablecoins is inevitable. But they’re saying the window to build alternatives is open now, not later. Regional data centers and local-currency tokenized money aren’t overnight projects. They take years. So the clock on a meaningful regional response is already running — whether ASEAN+3 governments treat it that way or not.
Fu and Huang put the thirteen-country group on notice: the AI economy is being built right now, and the currency layer is being decided alongside it.
Frequently Asked Questions
Who wrote the AMRO warning about AI stablecoins and dollar dominance?
The analysis was written by Chengxu Fu and Xiaguo Huang, economists at the ASEAN+3 Macroeconomic Research Office (AMRO).
Which countries does the AMRO report specifically address?
The report targets the thirteen ASEAN+3 nations: Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, Vietnam, China, Japan, and South Korea.
