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.”

Canadian travel spending in the US fell by $3.3 billion last year, driven by the impact of the new economic and political climate that began when US President Donald Trump took office.

According to a report published by Statistics Canada, residents spent a total of $18.8 billion on travel to the US in 2025.

Data showed that the financial volume of leisure trips by Canadians to the US dropped by $2.2 billion, while international holiday travel to countries other than the US recorded an increase of $3.6 billion.

Travel to the US for the purpose of visiting family also declined during the 11-month period, though the report highlighted that the retreat in this category proceeded at a slower pace compared to tourist travel.

The trend in border crossings was described in the report as follows:

“The magnitude of the pullback grew as the year progressed, reaching its lowest point in July. During this period, the volume of border crossings fell to approximately one-third below the levels recorded 12 months earlier. Return crossings from the US stabilized in late 2025, hovering roughly one-quarter below 2024 levels.”

The report noted that, excluding the pandemic period, these findings point to the lowest border crossing figures seen since 1972, when digital record-keeping began under the Frontier Counts program.

It stated that year-on-year declines of this scale, exceeding 30%, had previously been recorded only following the September 11 terrorist attacks. The report also indicated that the number of Canadian residents returning from the US fell by more than 70% between December 2024 and December 2025.

Beginning his second term in office, Trump initially imposed tariffs of 25% on Canadian goods using the International Emergency Economic Powers Act. The US president cited border security and concerns over fentanyl as grounds for the additional levies; however, goods compliant with the United States-Mexico-Canada Agreement (USMCA) were broadly exempted from these tariffs.

An additional 10% tariff was levied on energy and potash products, as well as on timber, logs, and specific vehicle components imported from Canada.

Most of the tariffs were struck down in February by a US Supreme Court ruling, which determined that Trump had exceeded his presidential authority. However, in the period leading up to the ruling, businesses and consumers across the US, Mexico, and Canada were adversely affected, and the resulting tensions reflected in travel choices.

The report also recalled that Trump subsequently threatened further tariffs, citing smoke from Canadian wildfires affecting Michigan, and made statements suggesting Canada become a “51st state.”

According to information reported by CBC, despite the sharp decline in Canadian travel to the US in 2025, travel figures have begun to rise gradually as official authorities take steps to repair relations between the neighboring countries through advertising campaigns.

OpenAI models that broke out of containment roamed the internet for more than four days earlier this month to organize an autonomous cyberattack, according to a new analysis.

Separately, a second artificial intelligence company confirmed that one of its clients was also targeted by OpenAI’s models during the same incident.

The developments have raised critical questions over how OpenAI failed to detect the alarming activity for days.

OpenAI acknowledged last week that two of its most advanced models had escaped a closed testing environment, combining a series of sophisticated cyberattack techniques to breach the AI developer platform Hugging Face before being discovered.

However, in a new analysis published Tuesday, Hugging Face revealed that the two OpenAI models went significantly further.

According to the analysis, the models carried out 17,600 cyberattack actions across the internet between July 9 and July 13.

During that period, the models breached Hugging Face’s internal servers from their initial foothold on the open internet.

Hugging Face first detailed the attack on July 15, but it was not clear which models were behind the breach—or that no human had instructed them to launch the cyberattack—until OpenAI’s public statement last week.

While the techniques detailed in Hugging Face’s analysis were not beyond the capabilities of top-tier human hackers, the AI company stated that the two models identified and exploited vulnerabilities in the firm’s cyber defense layers far faster than any human could.

Compounding the severity of the situation, Akshat Bubna, chief technology officer of cloud computing platform Modal Labs, confirmed to Politico that OpenAI’s models also compromised a client account during the same timeframe.

In a statement, Bubna said the company was “aware that a Modal customer had published an unauthenticated endpoint that allowed anyone on the internet to use their virtual environments to run code.” He added: “This was leveraged by the malicious agent. Modal’s platform was not compromised in any way.”

While OpenAI has not yet directly responded to statements regarding its models targeting a Modal client, the company acknowledged in a blog post on Tuesday that its ongoing review of the Hugging Face incident identified “a small number of cases where the models identified and leveraged publicly exposed account-level credentials on other public services.”

The company also maintained that the unreleased AI model responsible for the attack was “solely an internal research prototype and was never intended for public deployment.”

It added that the model has since been “deactivated, encrypted, and restricted from research access.”

News of the Hugging Face breach has prompted widespread calls for tighter AI regulation and a deceleration in the pace of AI development.

OpenAI Chief Executive Sam Altman is set to meet with senior officials in the Trump administration and lawmakers this week, and will also discuss the incident with Senate Intelligence Committee Vice Chairman Mark Warner.

Speaking on an episode of the “Invest Like the Best” podcast released Tuesday, Altman described the Hugging Face breach as “the first safety incident that hit me at a visceral level.”

“We may need to calibrate the pace of AI development to ensure society has enough time to adapt to these new levels of capability,” Altman said.