Anthropic launches enterprise AI spending reports as coding tool adoption grows

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Anthropic launches AI spending reports

Highlights

Anthropic launched new enterprise reporting tools on Wednesday, enabling detailed tracking of team outputs, costs, and recommendations without default model training on customer data.
Financial figures reveal Anthropic achieved operating profit in Q2 and reported 900% net revenue retention, projecting Q3 2026 customer spending to be nine times Q3 2025 levels.
Jellyfish data shows tools based on Anthropic models account for nearly a third of proposed code changes, with spending up tenfold this year to about 2% of total engineering cost.

New reporting tools target AI budget accountability

As reported by TechCrunch, Anthropic on Wednesday announces a new suite of reporting tools aimed at giving enterprise customers a more detailed view of the value they get from token spending.

Using internal analytics and employee surveys, managers can review a team's work across a selected date range, what that team produced, how much it cost, and where processes failed. Anthropic says the data is not used for model training by default, and the reports also include recommendations intended to improve results.

The company is also introducing pooled group budgets so teams can manage token spending more closely. The move is designed to address a growing demand from large customers for clearer evidence that AI deployments are generating measurable returns.

Enterprise stickiness strengthens Anthropic's position

Anthropic's push comes as businesses look for better ways to control rising AI costs, particularly in software development. Financial figures shared with investors this week suggest Claude Code is performing strongly, with the company recording operating profit in the second quarter and 900% net revenue retention, meaning spending from the same customers in Q3 2025 grows ninefold in Q3 2026.

Jellyfish, which makes tools for software developers, says in a report released Tuesday that Claude Code and other tools built on Anthropic models remain the most widely used in its survey of 276,000 customers. Those tools account for nearly a third of all proposed code changes submitted for review, while spending on them has risen 10 times since the start of the year and now equals about 2% of total engineering cost.

Jellyfish executives tell TechCrunch that many companies are moving from broad AI spending toward optimization, as switching costs rise once workflows are standardized around a provider. That dynamic may help Anthropic defend its lead with enterprise customers, even as competition from OpenAI and other frontier labs intensifies.

In our earlier article on a KPMG U.S. CEO survey about AI agents, we noted that many large companies are seeing efficiency and growth gains, but only a small share consider the technology transformational so far. The survey also highlighted continued investment in AI infrastructure, alongside hiring and retraining plans as organizations adapt processes and skills to make AI deployments deliver measurable value.

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