Anthropic launches tools to track enterprise AI spending

Anthropic’s financial disclosures to investors this week show just how much of a business Claude Code has become: the company posted an operating profit in the second quarter, and net revenue retention of 900% — meaning the same customers who were paying in the third quarter of 2025 are now spending nine times as much a year later.

On Wednesday, Anthropic used that enterprise traction as the occasion to launch a new suite of reporting tools, built on internal analytics and employee surveys, that let managers see what a team produced over a given period, what it cost, and where its workflows stalled. The reports include recommendations for improving results, and Anthropic says the underlying data will not be used for model training by default. The company is also rolling out pooled group budgets so teams can manage token spending collectively — a direct answer to large customers’ biggest complaint: proving the return on what they are spending. Businesses have been hunting for exactly that kind of visibility: spending from venture-backed startups is driving most of today’s AI token use, while most Fortune 500 firms report limited gains so far from deploying AI.

Independent data backs up the enterprise traction Anthropic is chasing. Jellyfish, which sells tools to software teams, published a report Tuesday based on 276,000 of its customers’ use of agentic coding tools: Claude Code and other Anthropic-based tools remain the most widely used in the survey, now showing up in close to a third of all code changes developers send out for review, and spending on them has grown 10x since the start of the year to about 2% of total engineering cost. “Even if you’re saying 2% is still small, that 10x growth is growth that most CFOs didn’t plan for,” Jellyfish chief scientist Nicholas Arcolano told TechCrunch.

That lead has held even as OpenAI’s Astra model, released this summer, looked like a potential threat; Jellyfish’s AI product lead, Nikolas Albarran, said Anthropic’s coding tools built up an incumbent advantage through deep enterprise integration work that makes switching costly, even when rival models are comparable. Anthropic’s new reporting suite works like a lighter version of that same hands-on support — the forward-deployed engineering teams AI labs use to embed consultants inside customer organizations — aimed at keeping already-dependent customers from drifting.

Why it matters

For Anthropic, measuring ROI is not just a customer favor — it is a retention tool. The harder it is for a company to show its AI spend is paying off without Anthropic’s own analytics, the harder it becomes to leave.