For the first time since the AI race began, more US businesses are paying for Anthropic’s cloud than for OpenAI’s ChatGPT.
According to the May 2026 release of the Ramp AI Index, Anthropic adoption among businesses increased by 3.8% in April to 34.4%. OpenAI adoption fell 2.9% to 32.3%. Overall AI adoption among businesses increased by 0.2 percentage points to 50.6%.
The crossover — published Tuesday by Ramp, a corporate card and finance automation platform that tracks spending patterns at more than 50,000 U.S. businesses — marks the culmination of a yearlong surge by Anthropic that few in the industry had predicted. Anthropic has quadrupled its business adoption over the past year, while OpenAI has only grown its business adoption by 0.3%.
But the same report that crowns a new market leader also warns that Anthropic’s position may be more fragile than it seems – threatened by rising costs, compute bottlenecks and the very token-based pricing model that has fueled the company’s extraordinary revenue growth.
How Anthropic went from being a niche player to the most popular AI model in corporate America
To appreciate the scale of the change, consider where both companies were a year ago. In April 2025, OpenAI commanded about 32% of business AI adoption, according to Ramp’s underlying data, while Anthropic had less than 8%. OpenAI had built an early, commanding lead as the consumer default – ChatGPT was where most people first encountered AI, and that momentum was carried into corporate purchasing decisions.
Anthropic’s path was different. The company was popular among early adopters – engineers, AI evangelists, technology leaders inside organizations. As Ramp chief economist Ara Kharazian noted in the March 2026 edition of the index, Anthropic took advantage of that early-adopter base to go mainstream. By February, Anthropic was winning nearly 70% of the head-to-head against OpenAI among businesses purchasing AI services for the first time – a complete reversal of the trends seen in 2025.
The trajectory is visible in the underlying data of the ramp. The company’s adoption data shows that Anthropic grew from 0.03% of businesses in June 2023 to 7.94% by April 2025, then increased to 34.44% by April 2026.
OpenAI, meanwhile, peaked at 36.5% in mid-2025 and has been slowly falling since then. The engine behind this growth is a single product: Cloud 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 written by cloud code – double the percentage from just a month earlier.
Business Insider reported in April that a crossover was imminent. A spokesperson for Ramp told the outlet this "At the current pace, Anthropic is on track to surpass OpenAI within the next two months." Given that it has already led "Early adopters, including VC-backed companies, and in key sectors such as software, finance and professional services." That prediction proved accurate almost to that day.
AI adoption has reached a tipping point in the workplace, but the productivity revolution isn’t here yet
The ramp up data on business spending is complemented by a separate workforce survey that underscores how deeply AI has embedded itself in American economic life. For the first time in Gallup’s measurement, half of employed US 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 Gallup data, based on a February 2026 survey of 23,717 US employees, also suggests that the benefits of AI remain focused at the level of individual tasks rather than organizational change. Only one in 10 employees in organizations that have adopted AI strongly agree that artificial intelligence has changed the way they work. This finding is consistent with firm-level studies in the US, UK, Germany and Australia, in which CEOs reported minimal broad productivity impacts from AI over the past three years – a notable gap between the hype cycle and operational reality.
The ramp method captures a different but complementary signal. Where Gallup asks employees if they use AI, Ramp measures whether their employer is writing checks for it. The index counts corporate card and invoice-based payments, with companies identified 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, both datasets paint a picture of AI that is ubiquitous in the American workplace but has not yet fulfilled its promise to fundamentally change the way organizations operate.
Why Anthropic’s biggest threat may be the success of its own best-selling product
Perhaps the most notable aspect of Ramp’s analysis is its refusal to declare a permanent winner. Kharazian identified three specific risks facing Anthropic even as the company takes the lead – and the most serious one arises from the structural tensions inherent in the company’s business model.
Anthropic makes more money when businesses purchase more tokens, meaning the company is incentivized to steer users toward more expensive models, even if cheaper models are sufficient. This dynamic is already causing budget crises in major enterprises. Uber’s CTO revealed that the company spent its entire 2026 AI budget in just four months, primarily on cloud code and cursors, with engineers estimating monthly API costs between $500 and $2,000 per person. Adoption by Uber engineers increased from 32% to 84% in just a few months, and about 70% of the code committed at Uber now comes from AI. The Uber case is a microcosm of a broader tension: Cloud code works – perhaps too well. When a productivity tool becomes so valuable that an organization’s $3.4 billion R&D operation is unable to keep the lights on, the resulting cost scrutiny can push enterprises toward cheaper alternatives.
Additionally, quality and reliability have suffered under the burden of demand. In recent weeks, users have experienced frequent outages, rate limits, and growing dissatisfaction with the cloud’s results. Anthropic has responded by resetting usage limits and striking a compute deal with SpaceX to access more than 300 MW of new capacity at the Colossus 1 data center in Memphis. CEO Dario Amodei said the company saw "80x increase in revenue and usage per year" For the first quarter of 2026, when it had planned only 10x. And Ramp economist Rafael Hajjar found that Anthropic’s latest model update will triple the token cost for any prompt that includes an image — a change that seems inconsistent with the company’s already serious cost and calculation problems.
Open-source models and OpenAI’s codex could quickly destroy Anthropic’s narrow edge
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 — providing enterprises a way to "is enough" AI at a fraction of the cost, especially for routine tasks that don’t require frontier model capabilities.
OpenAI’s codec presents an even more direct threat. By most measures, it’s a robust product that performs many of the same functions as cloud code at a lower price – and switching costs between models are minimal. Uber itself is already testing Codex as a defense, a move that could preview a broader pattern in enterprise technology. OpenAI also retains huge structural advantages. ChatGate reached 900 million weekly active users by March 2026, dwarfing the cloud’s consumer footprint. Enterprise revenue now makes up more than 40% of OpenAI’s total and is on track to catch up with consumer revenue by the end of 2026. And OpenAI’s $122 billion funding round, which closed in March at an $852 billion valuation, gives it vast resources to compete on pricing, capacity and product development.
is not constant on the anthropic distribution. AWS recently launched Cloud Platform on AWS, giving enterprises direct access to Anthropic’s core platform through existing AWS credentials, billing, and access control – a move that significantly reduces purchase friction. Anthropic has also announced compute agreements totaling billions of dollars with Amazon, Google, Microsoft, Nvidia and others, though the majority 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 of $900 billion.
This is the unexpected reason businesses are choosing the cloud over cheaper alternatives
Beneath the spend figures 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. Cloud Code and OpenAI’s Codex are broadly comparable products – on some benchmarks, Codex is arguably better, and it’s cheaper, too. Yet Anthropic cannot meet its demand. Each plan still has usage limits and rate caps. The company is actively forgoing revenue because it doesn’t have the calculations to cover it. Despite charging more for roughly equivalent performance, demand for Anthropic is growing.
Kharazian suggested that the answer may be cultural. Earlier this year, Anthropic refused to agree to the Pentagon’s terms of use for Claude, resulting in the Defense Department blacklisting it. OpenAI stepped in to offer its services in place of Anthropic. In the wake of that episode, users rallied in favor of Anthropic, and the cloud temporarily overtook ChatGPT on the App Store. The question is whether choosing an AI model is becoming less like an enterprise purchase decision, Kharazian wrote. "Like the green bubble/blue bubble difference in iMessage: a sign of identity and a choice of technology."
This observation may seem absurd for the enterprise software category. But the ramp data tells a story that pure economics can’t fully explain. In a market where 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 wrote in his report: "We have never seen the software industry so dynamic, where newcomers can disrupt market leaders in a matter of months, and where the pace of growth overwhelms the typical forces of vendor stickiness."
That dynamic cuts both ways. The same forces that drove a company from 8% to 34% market share in twelve months can just as easily do the opposite. Anthropic’s double-digit lead was earned in the most volatile software market in modern history – and in this market, the distance between the highs and the floor has never been smaller.
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