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Chronicles

The story behind the story

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Ramp data: 30.6% of US businesses paid for Anthropic's tools in March, up from 24.4% in February; OpenAI's US business adoption remained nearly flat MoM at ~35%

Divergence reflects company's recent rapid growth owing to strong interest in its Claude Code products

Financial Times Clara Murray

Context & Ripple Effects

Ramp’s earlier data showed Anthropic taking roughly 73% of spending from companies buying AI tools for the first time, after an earlier even split with OpenAI; the March figures extend that shift in new-buyer AI spending into broader paid-business adoption.

The comparison matters because Ramp had previously recorded substantial OpenAI subscription penetration among its card-using US businesses, making the current gap in month-to-month momentum a meaningful procurement signal rather than simply evidence of a new entrant gaining its first customers.

First-order effects

  • Anthropic’s paid footprint among Ramp-tracked US businesses expands quickly, with demand for Claude Code identified as the immediate driver.
  • OpenAI remains the more widely adopted service in this sample, but its nearly flat monthly adoption means Anthropic closes part of the gap rather than OpenAI extending its lead.

Second-order effects

  • Enterprise AI buyers evaluating coding workflows gain a clearer reason to test or add Anthropic alongside incumbent OpenAI subscriptions, reinforcing multi-vendor procurement rather than a winner-take-all purchase.
  • OpenAI faces more pressure to defend business usage in developer-facing workflows, while Anthropic can use the larger installed base to deepen team-level deployments and renewals.

Third-order effects

  • If first-time spending and paid adoption continue to move together, enterprise generative-AI competition may be decided increasingly by product-specific workflow fit—especially coding—rather than general-model familiarity alone.
  • Ramp-card data reflects one spending channel and adoption does not establish usage depth; nevertheless, sustained convergence would make enterprise model procurement a more contested, multi-supplier market.

The trend: This is one data point in the shift from broad enterprise experimentation with AI models toward workflow-led, managed-model purchasing decisions.