OpenAI and Anthropic Get 80% of Revenue From 1% of Customers

Enterprise artificial intelligence adoption is spreading, but the money is piling up fast among a small group of companies. New data from Ramp shows the top 1% of customers account for 80% of enterprise revenue at both OpenAI and Anthropic, a concentration that has held steady even as more businesses start paying for generative AI, Ramp lead economist Ara Kharazian said on X. “This is a level of concentration risk unseen in any other software category we track,” Kharazian said on LinkedIn.

At Anthropic, that concentration has a name attached to it. Coding tools Cursor and GitHub Copilot alone drove roughly $1.2 billion of the company’s $5 billion revenue milestone last year, close to a quarter of total revenue from just two customers, VentureBeat reported. One of those two customers, GitHub, is owned by Microsoft, which has also invested $13 billion in Anthropic’s biggest rival, OpenAI.

OpenAI’s disclosures show usage spread widely across its customer base: more than 9,000 organizations have processed over 10 billion tokens through its API, and nearly 200 have exceeded 1 trillion tokens each, OpenAI said in its State of Enterprise AI report. OpenAI has not disclosed what share of total revenue any single customer represents.

Anthropic’s broader base tells the same top-heavy story at scale. The company told investors it now has roughly 6,000 customers spending at least $100,000 annually, up sevenfold in a year, while customers spending at least $1 million annually more than doubled to over 1,000 in about two months, 24/7 Wall St. reported. Anthropic separately disclosed that its number of enterprise clients paying more than $1 million annually more than doubled in recent months to top 1,000, PYMNTS reported. Enterprise and startup API calls, priced by usage rather than a flat fee, drive roughly 80% of Anthropic’s total revenue, according to research firm Sacra, the same concentration Ramp’s data captured independently from the outside.

AI Spending Doesn’t Have to Stop at the Seat

That distinction matters because AI costs aren’t set simply by headcount. A conventional software contract is usually priced per seat. Adding AI into production adds another variable: how much the software actually does, the same dynamic that let two coding tools become a quarter of Anthropic’s business almost overnight.

That structure helps explain the uneven growth between labs. Enterprise API spending has shifted sharply toward Anthropic, now around 40% of the market against OpenAI’s 27%, according to Menlo Ventures’ 2025 State of Generative AI in the Enterprise report, up from just 12% in 2023 when OpenAI held 50%. Google has climbed to 21% over the same period, meaning three companies now account for roughly 88% of enterprise large language model (LLM) API usage combined, according to the same report. Menlo Ventures is itself an investor in Anthropic.

Top 1% Could Be a Preview for Other Industries

Financial services show where the next wave of heavier users could come from outside tech. Ninety-five percent of financial firms report broad or embedded use of newer AI in their data and technology work, according to a PYMNTS Intelligence August 2026 Enterprise AI Benchmark Report. Eighty percent of the firms expect spending to rise over the next 12 months, with none surveyed expecting to cut it, the same report found. The firms have also reached majority adoption in 27 of 75 tasks tracked, more than healthcare and media combined, PYMNTS reported separately.

The open question is whether that pattern spreads beyond companies built around technology, or stays concentrated in firms, like Cursor, built entirely around AI from day one. Banks, payments firms and retailers handle enormous transaction volumes, and even modest AI usage there could add up fast once systems move from pilots into production. But higher adoption doesn’t guarantee the same spending curve, and Anthropic’s own Cursor-and-Copilot dependency is a reminder of how much risk can sit inside a fast-growing revenue line.

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