Microsoft and Uber Discover AI Coding Tools Can Cost More Than the Human Workers They Were Supposed to Replace

The pitch was simple: AI coding tools would slash labor costs and pay for themselves many times over. Uber burned through its entire 2026 AI coding budget in four months after running internal leaderboards encouraging maximum tool usage — more adoption, more tokens, more compute, bigger bill. Microsoft, meanwhile, cancelled most of its Claude Code licences after thousands of engineers adopted the tool faster than anyone anticipated, a cost-control retreat from the company that literally built GitHub Copilot.

The structural problem is what happens when you charge per token and then actively incentivize consumption. Nvidia VP Bryan Catanzaro — someone with every financial reason to be bullish — admitted that for his own team, compute costs now exceed payroll. MIT research found AI is only economically viable for a narrow slice of well-defined, repetitive tasks; the long agentic sessions the industry has been most aggressively promoting are exactly where the math falls apart. Cheaper tokens haven't produced cheaper bills. They've produced more tokens.