Highlighting the growing impact of artificial intelligence across enterprise operations, Uber COO Andrew Macdonald said the company’s use of AI coding assistants such as Claude Code and ChatGPT has increased internal productivity by around 25%. However, he noted that the company has not yet seen a direct connection between those productivity gains and the delivery of more useful consumer-facing features.
According to reports, speaking on the Rapid Response podcast, Macdonald explained that while AI adoption has accelerated software development processes, it remains difficult to measure how those improvements directly translate into better products for riders and drivers.
“That link is not there yet,” said Macdonald. “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.’”
Uber reportedly exhausted its 2026 AI coding tools budget within just 4 months after encouraging employees to increase AI adoption through an internal leaderboard system. The surge in usage reflects a broader challenge facing enterprises, where AI adoption costs continue rising despite lower per-unit AI pricing.
Macdonald added, “If you’re not actually able to draw a direct line to how many useful features you’re shipping to your users, that trade becomes harder to justify.”
Other technology companies are also reassessing AI spending strategies. Reports suggest Microsoft has reduced Claude Code licenses and shifted engineers toward GitHub Copilot CLI, while Duolingo CEO Luis von Ahn has reportedly softened earlier expectations around AI replacing human tasks.
Uber CEO Dara Khosrowshahi recently revealed that nearly 10% of the company’s committed code is now generated by autonomous AI agents. He said AI tools are being used across engineering, legal, and marketing teams and described them as creating “employees with superpowers.”
During Uber’s first-quarter 2026 earnings call, Khosrowshahi stated that AI productivity gains are significant enough to shift spending priorities from workforce expansion toward AI tools and infrastructure investments.
“I think you should just look at AI as an accelerator,” Khosrowshahi said. “For us, for every company, it means that our investment in AI tools and infrastructure is increasing. That will be offset by slower headcount growth.”
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