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Home » Anthropic currently has more enterprise customers than OpenAI, according to Ramp data.
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Anthropic currently has more enterprise customers than OpenAI, according to Ramp data.

Editor-In-ChiefBy Editor-In-ChiefMay 13, 2026No Comments2 Mins Read
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For the first time, Anthropic has more verified enterprise customers than OpenAI, according to fintech company Ramp’s AI Index this month.

The study, compiled from Ramp’s client spending data, found that 34.4% of participating companies pay for Anthropic services, more than any other AI lab, and only 32.3% of companies pay for OpenAI.

This is the first time Anthropic has held the top spot.

“Anthropic is already leading among high-adoption groups such as finance, technology, and professional services,” Ramp economist Ara Kharazian told TechCrunch. “OpenAI still has a lead among other companies, but that lead has been shrinking over the past few months.”

This index only represents companies that use Ramp, so it is not a perfect proxy for the overall market. Still, the sample includes more than 50,000 companies, making it broad enough and diverse enough to convey significant weight.

More importantly, general trends are visible across industries. The last time OpenAI ranked higher than Anthropic on OpenRouter’s leaderboard, which samples different segments of users, was in December 2025.

The past 12 months have been particularly transformative for Anthropic, according to Ramp’s figures. As of May 2025, only 9% of businesses were paying for Anthropic products, but this number grew by 26% in the following 12 months. Over the same period, OpenAI’s share decreased by 1%, while the overall share of companies using some kind of AI product increased by 9%.

Karazian is skeptical that this advantage will last, for reasons he explained in a blog post, but said last year’s success is proof that Anthropic has chosen a good strategy.

“What Anthropic did was very successful,” Kharazian told TechCrunch. “It’s about starting with a very technical customer base, focusing on their needs, really successfully executing, and then starting to scale through tools like Cowork.”

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