Microsoft Cancelled Claude Code. Uber Ran Out of AI Budget.
Author: Protik Ganguly
Uber gave 5,000 engineers access to Claude Code in December 2025. By April, the company had exhausted its entire 2026 AI budget. Uber's CTO told The Information: "I'm back to the drawing board, because the budget I thought I would need is blown away already" (Fortune, 2026). Microsoft wound down most internal Claude Code licenses in mid-May, ending access for its Experiences and Devices division by June 30. Token-based billing made consumption unsustainable at deployment scale — just six months after the pilot launched.
These are not small companies making naive mistakes. These are two of the most sophisticated technology operators in the world. And they both discovered the same thing: AI tools that make engineers more productive also make AI bills unpredictable in ways that traditional procurement logic cannot handle.
The mechanism is specific. Claude Code operates on token consumption — costs vary based on how engineers actually use it. An engineer running basic autocomplete generates minimal spend. One orchestrating parallel agents across a large codebase can run up thousands of dollars in the same period. Monthly per-engineer costs at Uber ranged from $150 to $250 on average, with heavy users reaching $2,000 (DesignRush, 2026). Multiply across 5,000 engineers and the variability destroys any budget forecast built on averages.
Uber compounded the problem with an internal leaderboard that scored engineers by how many tokens they consumed. The more tokens, the higher the score. Engineers had every incentive to use Claude Code aggressively and no incentive to hold back. The company built a system that rewarded consumption without measuring value. The bills followed logically.
Uber's COO Andrew Macdonald was asked whether the spending connected to consumer-facing innovation. His answer: "That link is not there yet. Maybe implicitly there's more that is getting shipped, but it's very hard to draw a line between one of those stats and actually producing 25% more useful consumer features" (Fortune, 2026).
That is the AI productivity paradox expressed by a company living it in real time.
A 2025 Mavvrik survey found 85% of companies miss AI cost forecasts by more than 10%. Goldman Sachs forecasts a 24-fold increase in token consumption by 2030 as agentic AI scales (Fortune, 2026). The bills are not getting smaller. The measurement problem is not going away. Companies deploying AI fastest are discovering that speed of adoption and clarity of return are not the same thing.
The tools work. The economics are still being written.
References
Fortune. (2026, May 22). Microsoft reports are exposing AI's real cost problem. https://fortune.com/2026/05/22/microsoft-ai-cost-problem-tokens-agents/
Fortune. (2026, May 26). Uber burned through its entire 2026 AI budget in four months. Now its COO is questioning whether it's worth it. https://fortune.com/2026/05/26/uber-coo-ai-spending-tokens-claude-code/
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