Stripe executives say the artificial intelligence “singularity” has already arrived, explaining that a sharp acceleration in technology-driven business creation and other long-term trends convinced the payments company that the world entered a new economic phase at the beginning of 2026.

In a letter to investors on Wednesday, Stripe CEO Patrick Collison, President John Collison and President of Technology and Business William Gaybrick said the company had decided to treat January 1 as the beginning of the singularity, which is broadly used to describe a point at which artificial intelligence surpasses human intelligence and begins driving rapid, potentially unpredictable technological change.

“It’s a fuzzy and perhaps already overworked term, but we decided that January 1st marked the beginning of the singularity, and we have since been operating on that basis,” the executives wrote.

The claim puts Stripe among a growing group of prominent technology executives who believe AI has moved beyond an incremental improvement in software and into a period of accelerating economic and technological change.

The executives acknowledged that the term “singularity” is often associated with predictions of a dramatic technological rupture, but said Stripe’s decision was based on observable changes in the economy rather than a belief in a specific futuristic scenario.

“The singularity is often invoked alongside millenarian forecasts, but, in our case, we simply saw a large inflection in long-run trends,” they wrote, pointing in particular to “a huge increase in the rate of new firm creation.”

Rather than claiming that AI has definitively achieved a universally accepted threshold of superhuman intelligence, Stripe appears to be using “singularity” as an operating assumption for a period in which AI is materially changing the pace at which businesses are created, and technology is deployed.

The company says the shift is already having an impact on its own business.

Stripe reported that revenue increased 41% year over year in the first half of its fiscal year. The executives said the acceleration associated with AI appeared to be benefiting the company’s core payments business as more companies are created and existing businesses increase their digital activity.

“The singularity appears to be accelerating our core business,” they wrote.

Stripe’s timing is also notable because the company announced Wednesday that it was acquiring OpenRouter, an AI model marketplace startup. The acquisition was not mentioned in Stripe’s public announcement of the deal, but it reinforces the company’s broader push into the infrastructure surrounding the AI economy.

OpenRouter provides access to multiple AI models through a common platform, allowing developers to select and route requests between different models. Bringing such infrastructure into Stripe could strengthen the company’s position as AI companies and AI-powered businesses become increasingly dependent on automated payments, billing and financial services.

Stripe’s strategy goes beyond simply benefiting from the growth of AI companies.

The executives said the company has two objectives as artificial intelligence changes the economy: accelerate AI adoption and ensure that the deployment of AI gives individuals greater control over their economic lives.

That suggests Stripe sees AI as a potential catalyst for a much larger population of businesses, including companies that can be created and operated with far fewer employees than traditional firms.

The concept is relevant to Stripe because the company sits at the financial infrastructure layer of the internet. Every new software company, online marketplace, or AI-powered service that accepts payments potentially becomes a customer or transaction flowing through Stripe’s systems.

If AI substantially reduces the cost and time required to start a business, the resulting increase in company formation could create a larger addressable market for payment processing, financial services and business infrastructure.

This is the economic argument behind Stripe’s singularity thesis.

But the claim is not without sceptics.

OpenAI CEO Sam Altman said in July that humanity was already in the singularity, describing the development as potentially transformative. Tesla CEO Elon Musk made a similar declaration in January, writing on X that “We have entered the Singularity.”

Several AI researchers and experts have disputed such claims, arguing that there is no agreed definition or measurable threshold establishing that the singularity has occurred. That disagreement is partly semantic but also reflects a deeper debate about the current capabilities of AI.

Modern AI systems can perform tasks that previously required highly skilled human labor, including software development, research, analysis, and content generation. Yet they remain prone to errors, require human oversight in many important applications, and do not demonstrate a universally accepted form of general intelligence that would clearly establish that machines have surpassed humans across the board.

Stripe’s letter appears to sidestep that debate.

The company is not necessarily arguing that a machine has crossed a single scientific threshold. Instead, its executives are saying that the pace of economic change associated with AI has become large enough for the company to alter how it makes long-term business decisions.

That approach comes with both opportunities and risks.

Stripe’s executives acknowledged that the world could become harder to predict as technological change accelerates. They argued that Stripe’s status as a private company gives it greater flexibility to make long-term decisions without responding to the short-term demands of public markets.

“Stripe is, of course, a private company today. We view this as a growing advantage as we venture into the vicissitudes of the singularity,” the executives wrote.

“The world is becoming harder to predict and we expect that deft helmsmanship will be required of every company.”

The statement also pinpoints the unusual position of Stripe as it prepares for an increasingly AI-driven economy. Unlike AI model developers such as OpenAI and Anthropic, Stripe does not need to win the race to build the most capable model. Its opportunity is to provide the financial infrastructure for businesses that emerge from the technology.

That could include AI-native companies operated by very small teams, autonomous software agents conducting commercial transactions, new marketplaces and services built around AI-generated products, and traditional businesses using AI to increase productivity.

The potential scale of that market explains why Stripe is investing in AI infrastructure while simultaneously benefiting from the broader increase in business formation it believes the technology is producing.

But the company’s thesis also depends on AI generating sustained economic activity rather than simply a temporary wave of experimentation and venture investment.

If AI lowers the cost of starting businesses and allows companies to operate with fewer employees, Stripe could see a substantial increase in the number of merchants and transactions flowing through its network. If businesses instead consolidate around a small number of dominant AI platforms, the economic benefits could be distributed very differently.

For now, Stripe is positioning itself for the first scenario.

Its 41% first-half revenue growth, OpenRouter acquisition and decision to operate as though the singularity has already begun indicate that the company is treating AI as a structural change to the economy rather than another technology cycle.

Whether January 1, 2026 ultimately proves to have been the beginning of a genuine technological singularity is impossible to establish today. But Stripe’s decision to behave as though it has arrived is itself a notable signal from one of the world’s largest private financial-technology companies.

The U.S. Treasury’s efforts to ease pressure in the government bond market may provide temporary relief but will not address the deeper problem of rapidly rising debt issuance, according to JPMorgan.

James Sullivan, JPMorgan’s co-head of global fundamental research, said the Treasury’s strategy of buying back longer-dated bonds while financing itself with shorter-term bills could help manage borrowing costs in the near term, but ultimately leaves the government’s underlying debt burden unchanged.

“It’s a little bit like paying your mortgage with your credit card. It can work for a while, but eventually the mismatch starts to become more obvious,” Sullivan told CNBC’s “Squawk Box” on Friday.

The Treasury Department, led by Secretary Scott Bessent, announced Wednesday that it would at least double the size of its government debt buybacks. The programme is scheduled to run from Sept. 9 through Nov. 4.

The buybacks are designed to improve liquidity and manage the supply of longer-maturity Treasury securities. By purchasing older, less-liquid bonds, the Treasury can influence the composition of outstanding debt while issuing more short-term bills to meet its financing needs.

Sullivan argues, however, that this does not eliminate the central challenge facing global bond markets: an enormous volume of government and corporate debt that must ultimately be absorbed by investors.

“The only way you balance supply and demand is through price,” he said.

In bond markets, that price adjustment is reflected largely through yields. If the supply of debt rises faster than investor demand, issuers generally have to offer higher yields to attract buyers. That creates a potential feedback loop for governments because higher yields increase the cost of servicing existing and newly issued debt.

The issue extends well beyond the United States. Sullivan pointed to roughly $40 trillion of U.S. government debt and about $76 trillion of government debt across developed markets, alongside record corporate bond issuance.

“Governments trying to control markets is not a particularly attractive story most of the time,” Sullivan said.

One of the concerns is that some traditional buyers of U.S. government debt are reducing their exposure. China’s Treasury holdings have fallen to an 18-year low, while U.S. Treasury custody holdings for foreign governments are at their lowest level in 14 years. That means the Treasury could face a more difficult funding environment as it competes for capital with other sovereign issuers and increasingly large corporate borrowers.

The pressure is notable because the borrowing surge is occurring alongside a major investment cycle in artificial intelligence and other capital-intensive industries. Companies are increasingly issuing debt to finance data centers, semiconductor facilities and other AI infrastructure, as well as investment associated with reshoring manufacturing and national security. AI companies alone have issued about $200 billion of debt so far this year, according to Sullivan, an 80% increase from a year earlier.

That additional corporate borrowing creates another source of competition for investors’ money. A pension fund, asset manager or other institutional investor allocating capital to corporate bonds is potentially allocating less to government bonds or equities, while higher Treasury yields can force companies to offer still higher returns to attract financing.

The consequences are also spilling into equity markets.

Higher Treasury yields increase the attractiveness of bonds relative to stocks, particularly when equity valuations are elevated. Investors can demand a greater expected return from stocks when government bonds provide higher yields with considerably less credit risk.

According to JPMorgan data, Treasury yields are now above the earnings yield on the S&P 500. The earnings yield is the inverse of the market’s price-to-earnings ratio and provides a simple way of comparing the income generated by equities with the return available from bonds.

That relationship makes the asset-allocation decision more difficult for investors. If Treasury yields continue to rise, equities may need either stronger earnings growth or lower valuations to remain competitive.

“The asset allocation decision becomes significantly more complex going forward as we see these environments play out,” Sullivan said.

The Treasury’s buyback programme could therefore help smooth market conditions without resolving the structural imbalance. By shifting issuance toward shorter maturities, economic experts say the government can reduce some pressure at the long end of the curve, but it also increases its exposure to refinancing risk because short-term debt must be rolled over more frequently.

That distinction is becoming more glaring as the government seeks to finance a large fiscal deficit while long-term investors demand greater compensation for holding Treasury securities. The broader concern for markets is not simply the absolute level of U.S. government debt but the amount of new debt that needs to be absorbed at a time when governments and corporations around the world are competing for the same pool of savings.

If investor demand fails to keep pace with issuance, the adjustment mechanism will ultimately be higher yields. That could raise government financing costs, increase corporate borrowing expenses, and place further pressure on stock valuations.