AI infrastructure boom risks entrenching US dollar dominance in global economy, economists warn

While politicians and economists debate the future of US dollar hegemony, artificial intelligence may already be reinforcing it.

Writing for Project Syndicate, Chenxu Fu and Xianguo Huang argue that immediate action is needed to address the growing influence of AI companies, cloud service providers, and payment networks, which they say are already authoring “the next chapter of international monetary history.”

“The signing of a 20-year data center lease is unlikely to be perceived as a monetary event. Even the announcement of a dollar-pegged stablecoin linked to the AI boom may not necessarily be characterized as such,” the authors write. Nevertheless, they warn that such developments are spreading rapidly, contributing to the creation of a framework in which “an input vital to the global economy is priced, paid for, and ultimately converted into dollar-denominated assets.”

Fu and Huang note that since the 1970s, the pricing of oil in US dollars has driven global demand for the currency while generating export revenues for oil producers. Pointing out that the petrodollar serves not as a mere “prophecy” but as a “template,” they write:

“This demonstrates that when production, payments, and asset recycling reinforce one another, an indispensable input can embed a currency into global markets.”

Emphasizing that artificial intelligence could trigger its own distinct version of this dynamic, the authors observe that debates over who will win the AI economy typically focus on the race to develop the most advanced models. However, they argue that the real transformation begins “when model performances converge and companies integrate AI into their daily operations.”

“At that point, just as we speak today of dollars per barrel, we may find ourselves thinking in terms of dollars per unit of compute,” Fu and Huang write.

Turning their focus to energy, the authors emphasize that data centers convert electricity into “billable computing capacity,” noting that this capacity is “now being secured years in advance.”

For instance, when Anthropic signed a 20-year lease agreement with infrastructure provider TeraWulf, the move closely resembled an industrial firm securing long-term production capacity. According to the authors, this represents “a supply-side bet that demand for compute will persist.”

Project Syndicate notes that OpenAI’s new consulting arm, Deployment Company (DeployCo), aims to address slack on the demand side by embedding engineers directly within companies to integrate AI into their workflows. “Once such systems are deployed, compute expenses will become a recurring operating expenditure,” the publication states, before turning to the currency implications:

“This brings us to the first channel that will consolidate dollar dominance. If the AI supply chain is dominated by US-linked companies and pricing is executed in dollars, global digital production will be forced to secure dollar liquidity, and the resulting revenues will largely flow into a dollar-based financial system. Unlike oil revenues, these earnings will not accumulate abroad before returning to US markets.”

Beyond visible costs, the authors argue that an invisible infrastructure is being constructed underneath: a payment network upon which autonomous trade will increasingly operate.

OpenAI’s partnership with Visa aims to build this infrastructure, pointing toward a “more programmable” future.

“If AI agents begin purchasing services, arranging logistics, and replenishing inventory with minimal human intervention, payments must be automated and machine-native,” the authors write.

According to Fu and Huang, this represents the second channel reinforcing dollar dominance. Pointing specifically to dollar-pegged stablecoins, they emphasize that these tokens could provide “the programmable settlement solution required for smart contract-based commerce.”

The announcement of Open USD—a dollar-pegged stablecoin backed by more than 140 payment, financial, and cryptocurrency companies—demonstrates that dollar-based tokens are already being positioned for this transformation.

Acknowledging that these two channels could converge over time, the authors explain that the same system enabling “agent-based commerce” via dollar-pegged stablecoins could just as easily facilitate compute payments.

Consequently, dollar-based billing would merge with stablecoin payments, effectively converting technological dependence into monetary dependence.

This infrastructure also serves an asset-recycling function, as demand for programmable dollars translates into demand for the safe assets backing them—specifically US Treasuries.

While agent-based commerce is still in its infancy, stablecoin issuers are already among the largest buyers of US Treasury bills.

According to the authors, these combined developments point to the potential emergence of an “energy-compute-dollar loop”:

“Electricity powers data centers; data centers generate compute power; compute power enables the automation of business activities, including payments supporting programmable settlement; and stablecoin reserves flow into US Treasuries. Ultimately, a self-reinforcing cycle connecting AI infrastructure, digital payments, and US financial markets will emerge.”

Fu and Huang write that it is striking how no single government appears to be steering this process.

Whereas the petrodollar was established through formal agreements, they argue that the emerging AI-driven era is largely being shaped by commercial decisions:

Cloud service providers secure land and power resources. AI companies package models into services. Payment consortia build stablecoin infrastructure. Stablecoin issuers buy US Treasury bills.

“Each step makes sense on its own; but taken together, they quietly reinforce dollar dominance,” they write.

Noting that this reality carries major implications for non-US policymakers, the authors highlight existing regional countermeasures: “For example, ASEAN+3 countries are attempting to conduct trade in local currencies, connect national payment systems, and pool reserves to hedge against dollar shortages.”

However, Fu and Huang believe that while ASEAN+3 may not be able to prevent the formation of a “self-reinforcing dollar loop,” the bloc can limit its reliance on the currency:

“The key will be to unify energy, AI, and payments under a single strategic agenda. Regional data centers powered by affordable and increasingly clean energy could expand local firms’ access to compute resources. Furthermore, developing local-currency tokenized payment systems for agentic commerce would reduce dependence on dollar systems and ensure transactions remain traceable by regulators.”

Arguing that complete technological self-sufficiency is unrealistic for non-US countries in the near term, Fu and Huang contend that “the primary objective is to participate in digital production without accepting a new layer of dollar dependence as the price of admission. After all, unlike petrodollar arrangements, the emerging AI system offers nations no seat at any summit table.”

The authors conclude:

“While policymakers and economists debate the future of dollar dominance, AI companies, cloud providers, and payment networks may already be writing it into the next chapter of international monetary history. Those hoping to shape this chapter must act now; otherwise, they risk being left off the page.”