Anthropic just launched tools to show companies what their AI spending is buying

Anthropic on Wednesday introduced a suite of reporting tools that lets enterprise customers see what their spending on its models actually produces. The launch comes as the company disclosed financials to investors this week, including an operating profit in the second quarter and 900% net revenue retention, meaning spending from the same customers grew nine times between Q3 2025 and Q3 2026. The timing also precedes a planned IPO.

The tools draw on internal analytics and employee surveys. Managers can review a team's work over a chosen date range, what the team produced, its cost, and where workflows broke down. Anthropic says reports will include recommendations for improving results, and that it will not use the underlying data for model training by default. Alongside the reporting, the company is introducing pooled group budgets so teams can manage token spending collectively.

Anthropic is explicitly framing the release as a demonstration of return on investment, an issue large customers have pressed hard. That pressure is growing because usage among venture-backed firms is driving token spend while most of the Fortune 500 have not yet seen major gains from deploying AI. Jellyfish, which builds developer tooling, published a report Tuesday based on agentic coding tool use across 276,000 of its customers. Claude Code and other tools built on Anthropic models accounted for nearly a third of all proposed code changes submitted for review, and spending on those tools has grown 10x since the start of the year, now equal to roughly 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," said Nicholas Arcolano, Jellyfish's chief scientist. He told TechCrunch that customers are reaching the point where simply spending heavily is insufficient — spend now has to be optimized.

Competitive pressure appears real on social media but muted in Jellyfish's data. OpenAI's Astra model launched this summer and was seen as a potential threat, yet Anthropic's adoption numbers have held. Nikolas Albarran, Jellyfish's AI product lead, said Codex took a long time to register in their data and only moved after Astra's release, adding that Anthropic benefited from strong enterprise motions and incumbent weight, with many customers having standardized workflows around its tools and seeing no compelling reason to switch. Albarran also noted that all major AI labs are investing in forward-deployed engineering teams that embed consultants inside customers, and framed Anthropic's new reports as a lighter, "FDE-lite" version of that hands-on support.

What to watch: whether the pooled budgets and ROI reports meaningfully slow the 10x cost curve CFOs did not plan for, and whether Altman-competitive releases like Codex and Astra eventually crack standardization that Anthropic's enterprise motion has locked in ahead of the IPO.