For the first time since the AI race began, more American businesses are paying for Anthropic’s Claude than for OpenAI’s ChatGPT.

Adoption of Anthropic rose 3.8% in April to 34.4% of businesses, according to the May 2026 release of the Ramp AI Index. OpenAI’s adoption fell 2.9% to 32.3%. Overall AI adoption among businesses rose 0.2 percentage points to 50.6%.

The crossover — published Tuesday by Ramp, the corporate card and finance automation platform that tracks spending patterns across more than 50,000 U.S. businesses — marks the culmination of a yearlong surge by Anthropic that few in the industry predicted. Anthropic has quadrupled its business adoption over the past year, while OpenAI grew its business adoption by only 0.3%.

But the same report that crowns a new market leader also warns that Anthropic’s position may be more fragile than it appears — threatened by escalating costs, compute constraints, and the very token-based pricing model that has fueled the company’s extraordinary revenue growth.

How Anthropic went from a niche player to the most popular AI model in corporate America

To appreciate the scale of the shift, consider where the two companies stood a year ago. In April 2025, OpenAI commanded roughly 32% of business AI adoption according to Ramp’s underlying data, while Anthropic stood at under 8%. OpenAI had built an early, commanding lead as the consumer default — ChatGPT was where most people first encountered AI, and that momentum carried into corporate purchasing decisions.

Anthropic’s path was different. The company was popular early on with the earliest adopters — engineers, AI evangelists, the technical vanguard inside organizations. As Ramp lead economist Ara Kharazian noted in the March 2026 edition of the index, Anthropic leveraged that early-adopter base to go mainstream. By February, Anthropic was winning about 70% of head-to-head matchups against OpenAI among businesses purchasing AI services for the first time — a complete reversal of the trends observed in 2025.

The trajectory is visible in Ramp’s underlying data. The company’s adoption figures show Anthropic climbing from 0.03% of businesses in June 2023 to 7.94% by April 2025, then rocketing to 34.44% by April 2026.

OpenAI, meanwhile, peaked near 36.5% in mid-2025 and has been slowly declining since. The engine behind much of this growth is a single product: Claude Code, the company’s agentic AI coding tool, which has become the fastest-growing product in Anthropic’s history. A recent analysis estimated that 4% of all GitHub public commits worldwide were being authored by Claude Code — double the percentage from just one month prior.

Business Insider reported in April that the crossover was imminent. A Ramp spokesperson told the outlet that “at the current pace, Anthropic is on track to surpass OpenAI within the next two months,” noting that it already led “among early adopters, including VC-backed companies, and in key sectors like software, finance, and professional services.” That prediction proved accurate almost to the day.

AI adoption reaches a workplace tipping point, but the productivity revolution hasn’t arrived yet

The Ramp data on business spending finds its complement in a separate workforce survey that underscores just how deeply AI has embedded itself into American economic life. For the first time in Gallup’s measurement, half of employed American adults say they use AI in their role at least a few times a year, up from 46% the previous quarter. Frequent use is also increasing, with 13% of employees now saying they use AI daily and 28% reporting they use it a few times a week or more.

But the Gallup data, based on a February 2026 survey of 23,717 U.S. employees, also suggests that the benefits of AI remain concentrated at the level of individual tasks rather than organizational transformation. Only about one in 10 employees in AI-adopting organizations strongly agree that artificial intelligence has transformed how work gets done. That finding is consistent with firm-level studies across the U.S., U.K., Germany, and Australia showing chief executives reporting minimal broad productivity effects from AI over the past three years — a notable gap between the hype cycle and operational reality.

The Ramp methodology captures a different but complementary signal. Where Gallup asks employees whether they use AI, Ramp measures whether their employer is writing checks for it. The index counts corporate card and invoice-based payments, identifying firms as AI adopters if they have a positive transaction amount for an AI product or service in a given month. As Ramp’s methodology page notes, its results likely underestimate actual adoption because many employees use free AI tools or personal accounts for work tasks. Taken together, the two datasets paint a picture of AI that is ubiquitous in the American workplace but has not yet delivered on its promise to fundamentally transform how organizations operate.

Why Anthropic’s biggest threat might be the success of its own best-selling product

Perhaps the most striking aspect of Ramp’s analysis is its refusal to declare a lasting winner. Kharazian identified three specific risks facing Anthropic even as the company takes the lead — and the most serious one stems from a structural tension baked into the company’s business model.

Anthropic makes more money when businesses purchase more tokens, meaning the company is incentivized to drive users toward more expensive models even when cheaper ones are sufficient. This dynamic is already creating budget crises at major enterprises. Uber’s CTO revealed that the company spent its entire 2026 AI budget in just four months, largely on Claude Code and Cursor, with engineers reporting monthly API costs between $500 and $2,000 per person. Adoption jumped from 32% to 84% of Uber engineers in a matter of months, and about 70% of committed code at Uber now comes from AI. The Uber case is a microcosm of a broader tension: Claude Code works — perhaps too well. When a productivity tool becomes so valuable that an organization’s $3.4 billion R&D operation can’t afford to keep the lights on, the resulting cost scrutiny could push enterprises toward cheaper alternatives.

At the same time, quality and reliability have suffered under the weight of demand. In recent weeks, users have experienced frequent outages, rate limits, and increasing dissatisfaction with Claude’s results. Anthropic has responded by resetting usage limits and by striking a compute deal with SpaceX to access more than 300 megawatts of new capacity at the Colossus 1 data center in Memphis. CEO Dario Amodei said the company saw “80x growth per year in revenue and usage” for Q1 2026, when it had only planned for 10x. And Ramp economist Rafael Hajjar found that Anthropic’s latest model update would triple token costs for any prompt that includes an image — a change that seems at odds with the company’s already-acute cost and compute problems.

Open-source models and OpenAI’s Codex could quickly erode Anthropic’s narrow lead

The Ramp report points to competitive dynamics that could reshape the market within months. Some of the fastest-growing vendors on Ramp’s platform in April were AI inference platforms that give companies access to cheap, open-source models — offering enterprises a way to get “good enough” AI at a fraction of the cost, particularly for routine tasks that don’t require frontier model capabilities.

OpenAI’s Codex presents an even more direct threat. By most measures, it is a strong product that does many of the same tasks as Claude Code at a lower price point — and the switching cost between models is minimal. Uber itself is already testing Codex as a hedge, a move that could preview a broader pattern across enterprise tech. OpenAI also retains enormous structural advantages. ChatGPT reached 900 million weekly active users by March 2026, dwarfing Claude’s consumer footprint. Enterprise revenue now makes up more than 40% of OpenAI’s total and is on track to reach parity with consumer revenue by the end of 2026. And OpenAI’s $122 billion funding round, closed in March at an $852 billion valuation, gives it vast resources to compete on pricing, capacity, and product development.

Anthropic is not standing still on distribution. AWS recently launched Claude Platform on AWS, giving enterprises direct access to Anthropic’s native platform through existing AWS credentials, billing, and access controls — a move that lowers procurement friction considerably. Anthropic has also announced compute agreements totaling billions of dollars with Amazon, Google, Microsoft, Nvidia, and others, though much of that capacity won’t come online until late 2026 or 2027. Anthropic is reportedly in talks to raise another $50 billion at a valuation approaching $900 billion.

The unlikely reason businesses are choosing Claude over cheaper alternatives

Beneath the spending data and market share charts lies a more intriguing question: Why are businesses choosing Anthropic over a cheaper, comparably performing alternative?

Kharazian explored this in his March analysis. Claude Code and OpenAI’s Codex are roughly comparable products — on certain benchmarks, Codex is arguably better, and it’s also cheaper. Yet Anthropic can’t meet its own demand. Every plan still has usage limits and rate caps. The company is actively turning away revenue because it doesn’t have the compute to serve it. Despite charging more for roughly equivalent performance, Anthropic’s demand is growing.

Kharazian suggested the answer might be cultural. Earlier this year, Anthropic refused to agree to the Pentagon’s terms of use for Claude, resulting in a blacklisting by the Department of Defense. OpenAI stepped in to offer its services in Anthropic’s place. In the wake of that episode, users rallied around Anthropic, and Claude temporarily surpassed ChatGPT on the App Store. The question, Kharazian wrote, is whether choosing an AI model is becoming less like an enterprise procurement decision and “more like the green bubble/blue bubble distinction in iMessage: a signal of identity as much as a choice of technology.”

That observation may sound absurd for an enterprise software category. But Ramp’s data tells a story that pure economics cannot fully explain. In a market where the products perform similarly, where the cheaper option is arguably better on benchmarks, and where switching costs are negligible, something other than spreadsheet logic is driving the biggest shift in AI market share since the industry began. As Kharazian noted in his report: “We have never seen a software industry as dynamic, where newcomers can disrupt market leaders in a matter of months, and where the pace of development overrides the typical forces of vendor stickiness.”

That dynamism cuts both ways. The same forces that propelled a company from 8% to 34% market share in twelve months could just as easily work in reverse. Anthropic’s two-point lead was earned in the most volatile software market in modern history — and in this market, the distance between the throne and the floor has never been shorter.