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Tech Consumer Journal > News > AI Investment Is ‘Harder to Justify’ as Productivity Returns Lag, Uber COO Says
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AI Investment Is ‘Harder to Justify’ as Productivity Returns Lag, Uber COO Says

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Last updated: May 26, 2026 7:56 pm
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Uber does not see a link between productivity gains and its colossal AI spending commitments, according to the company’s chief operating officer.

Like much of the rest of the tech industry, Uber went all in on AI this past year. Company executives had employees across divisions embed AI into their workflows and reported that they were relying on AI agents for 10% of all code changes.

While Uber doesn’t outwardly subscribe to this practice, many tech giants have reportedly begun incentivizing more AI use among their employees with internal token use leaderboards. In March, Nvidia CEO Jensen Huang argued that if you hire a software engineer for $500,000 a year, they should be consuming “at least $250,000 worth of tokens” in that same time frame.

But tokens cost money, and it’s supposed to come from somewhere. Most executives have found that “somewhere” to be their own employees.

‘Somebody’s paying the bill’ for AI underperformance

Last month, Uber CTO, Praveen Neppalli Naga, told The Information that Uber had already exceeded its 2026 AI budget within the first four months of the year. Shortly after, at the company’s earnings call earlier this month, executives said that Uber would be upping that AI spending even further and slowing down hiring to help pay for it.

But now, Uber COO Andrew Macdonald says that those towering financial commitments are not directly correlating with real, tangible productivity gains, and it’s making it tougher to justify the headcount reductions.

“You talk to your senior engineering leaders, and you’re saying, ‘Okay, how many projects that were on the cutting room floor got moved above the line because of the productivity gains, because 25% of our code commits were via Claude Code last quarter,’ that link is not there yet,” Macdonald told the Rapid Response podcast over the weekend. “If you’re not actually able to draw a direct line to how much useful features and functionality you’re shipping to your users, that trade becomes harder to justify.”

Macdonald’s comments echo long-held worries about the AI boom and its murky productivity returns. Companies across industries are spending staggering amounts of money to adopt AI and have it automate tasks across workflows, hoping for unbelievable returns on productivity and new highs for profit.

The thinking among executives goes that because AI can work super fast and around the clock, and it doesn’t have the same needs as a human employee does, then surely it must be the wiser economic decision to have agents take over workflows instead.

But while AI can feel like it’s free for those who are using it, Macdonald said, “somebody’s paying the bill.” The AI industry has promised that the bill and the sacrifices made to pay for it will be worth it, but that scenario hasn’t panned out as quickly as promised.

Concern around U.S. economy’s pivot to AI is growing

Another way the Uber executive says he’s seen AI’s lack of return is through the rise of commerce AI agents. As agentic AI gains ground, some experts started sounding the death knell for app providers like Uber and DoorDash, whose business models they say will be completely disrupted by agentic AI assistants that will shop on behalf of the average user.

“We’re working with pretty much all of the large model companies as they roll out, try to roll out commerce, and there hasn’t really been anything that’s taken off yet,” Macdonald said. “It doesn’t mean it won’t happen, but a year ago at our board meeting, we were worried that by this point, a year later, we’d be totally disaggregated, because all commerce is going to be flowing through the large model codes in the form of chatbots, and that just hasn’t played out yet.”

Uber is only one, though rather major, addition to a growing trend that’s reportedly forming: even though the entire business world seems bullish on AI, its productivity returns are not following suit for everyone. If that trend continues, that has potentially disastrous consequences for the unprecedented AI infrastructure buildout this country is undertaking and the entire U.S. economy that AI spending has been propping up.

Read the full article here

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