Uber COO says AI spending isn’t yielding results

Uber COO and CTO Question ROI as AI Coding Costs Spiral

Uber is grappling with a widening gap between its AI spending and measurable productivity gains, with two of its most senior executives publicly raising concerns about the company’s return on investment in artificial intelligence tools.

COO Questions “Tokenmaxxing” Returns

In a Rapid Response interview released on Saturday, Uber’s chief operating officer Andrew Macdonald said it was becoming harder to justify the company’s escalating AI expenditures. Macdonald said that based on conversations with Uber’s senior engineering leaders, he realized higher token usage did not translate into a proportional increase in useful consumer features.aol

The remarks put a name to a growing concern in Silicon Valley: “tokenmaxxing,” or the drive to spend as many AI tokens as possible in the belief that more usage automatically means more output. Macdonald’s comments suggest that even companies deeply invested in AI tooling are beginning to question whether raw consumption correlates with business value.businessinsider

Budget Blown by April

Macdonald’s skepticism follows a disclosure by Uber CTO Praveen Neppalli Naga in April that the company had already exhausted its entire 2026 AI coding budget — just four months into the year. “I’m back to the drawing board because the budget I thought I would need is blown away already,” Neppalli Naga told The Information.theinformation

The overshoot was driven by aggressive adoption of Anthropic’s Claude Code across roughly 5,000 engineers after the tool was introduced in December 2025. Monthly API costs per engineer ranged from $500 to $2,000 for heavy users, with 95 percent of Uber’s engineers now using AI tools monthly and approximately 70 percent of committed code being AI-generated. Some 11 percent of live backend code updates are now written entirely by AI agents without direct human input.forbes

Balancing Innovation and Discipline

In May, Business Insider reported that Uber was slowing hiring to help fund its AI investment, a sign that the budget blowout is reshaping resource allocation across the company. The internal debate mirrors a broader industry reckoning: a Jellyfish analysis published in May found that while token usage boosts raw coding output, extreme consumption delivers diminishing returns.businessinsider

The tension between Uber’s COO flagging a lack of proportional consumer benefit and its engineering organization’s enthusiastic adoption of AI coding tools underscores the challenge facing technology companies attempting to translate generative AI spending into durable competitive advantage.