In a recent interview on the Rapid Response podcast, Uber president and chief operating officer Andrew Macdonald said it’s hard to draw a connection between the company’s rising use of Claude Code and innovations meant to serve consumers.

“That link is not there yet,” he said. “Maybe implicitly there’s more that is getting shipped, but it’s very hard to draw a line between one of those stats and ‘Okay now we’re actually producing like 25% more useful consumer features.’”

The comments follow reports that the firm had already burnt through its entire 2026 AI coding tools budget in just four months after incentivizing employees to adopt the technology through an internal leaderboard ranking teams by total AI tool usage. It’s the latest development in a complex quandary arising in enterprise AI adoption: increasing AI use comes with higher costs, even as per-unit AI pricing falls. 

“If you’re not actually able to draw a direct line to how [many] useful features and functionality you’re shipping to your users, that trade becomes harder to justify,” Macdonald said.

Uber isn’t the only company facing this issue. Microsoft earlier this month reportedly began canceling most of its direct Claude Code licenses, according to The Verge, instead moving engineers toward using GitHub Copilot CLI. A number of other business leaders have walked back their initial bullish AI views. Duolingo CEO Luis von Ahn last year reversed his outlook on AI, saying he doesn’t see the tech replacing the tasks his employees perform.

Uber didn’t immediately respond to Fortune’s request for comment.

Can firms justify their AI spending?

In an earnings call earlier this month, Uber CEO Dara Khosrowshahi said about 10% of the company’s committed code is built by autonomous agents. Though he added that the firm’s AI use extends beyond its software engineers. 

“We’re seeing uptake of these tools, whether it’s our legal team or marketing team or developers,” he said. “We think it’s creating employees with superpowers.” 

But with more AI use comes higher costs. A recent study from research firm Gartner found that by 2030, inference on highly sophisticated AI models will cost AI firms 90% less than 2025 costs. But the research also found cheaper tokens won’t translate to cheaper enterprise AI because agentic models require far more tokens per task than standard models, and because AI providers won’t fully pass through lower costs to consumers.

Some AI firms are shifting pricing plans to capture increased AI usage. Anthropic changed its pricing model, moving away from a flat fee to a usage-based model, meaning autonomous agents are now charged per token of compute use. In March, OpenAI CEO Sam Altman articulated the industry’s broader direction during an interview. 

“We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter,” he said.

A separate Gartner study forecasts AI agent software spending will reach nearly $207 billion in 2026, up more than 139% from the $86.4 billion spent in 2025.

Uber spent 3.4% on research and development in 2025, a 9% increase from 2024. The company spent $951 million on research and development in the first quarter of 2026 alone, a nearly 17% increase from the same time a year ago. 

Still, Uber isn’t shying away from technological innovation. Macdonald said the firm is going all in on autonomous driving, something he sees becoming the norm in under a couple decades.

“I don’t think my daughters who are little kids today, I don’t think they will end up getting a driver’s license,” he said.