TECHNOLOGY

Bosses Are Blowing More Money on AI Agents Than It’d Cost Them to Just Pay Human Workers

April 27th, 2026

Mindlessly unleashing AI agents to take over employees’ jobs can be pretty costly, it turns out. Some companies are learning the hard way that paying for the incredible volume of AI agent requests is costing more than what they’d pay their human employees, Axios reports.

AIs can perform all sorts of tasks, ranging from the rote to the complex. But one of the most popular ways it’s being used in the workplace is to generate mountains of code at a pace far greater than a human could achieve. Sometimes, software engineers will even run multiple AI agents at the same time, all working on different tasks in the background without supervision. Each of these tasks costs tokens, and the bill can quickly add up.

“For my team, the cost of compute is far beyond the costs of the employees,” Bryan Catanzaro, vice president of applied deep learning at Nvidia, told Axios.

The problem has become harder to ignore as organizations are increasingly reliant on using AI tools and agents — including the organizations building them. “Pretty much 100 percent” of Anthropic’s code is now AI-generated, the company’s head of Claude Code Boris Cherny claimed earlier this year. Google and Microsoft’s bosses claim that this share is around a quarter of their companies’ code. Meta employees performance reviews are now partly based on how much AI they use, showing that a lot of the push towards using AI is coming from the top.

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It probably doesn’t help that many tech workers are treating their token bills as member-measuring contests, using millions of tokens in a single day. The slang for this, we regret to inform you, is “tokenmaxxing,” with some power users racking up monthly token bills north of $150,000. “I probably spend more than my salary on Claude,” Max Linder, a software engineer in Stockholm, told The New York Times last month. Uber engineers using Claude Code have already blown through the company’s entire 2026 AI budget, The Information reported.

Tech leaders’ attempts to grapple with the situation can sound nearly as comical as the dilemma itself. In March, Nvidia CEO Jensen Huang proposed giving software engineers AI tokens equal to roughly half their base salary, something he said could be used as a recruiting tool. Why be wooed by a signing bonus, when if you work for us, you get to use more AI?

At the same time, it’s a clear money-making opportunity for AI providers. One OpenAI investor told Axios that the concern over token costs could benefit them, since they believe Codex uses tokens more efficiently than Anthropic’s Claude Code. Anthropic, meanwhile, has cashed in by raising its pricing.

In all, the token costs are just one of many major question marks over AI automation. The jury’s still out on whether using error-prone AIs is more efficient and worth the potential havoc they can wreak internally — as evidenced by incidents at Meta and Amazon, among others — while numerous studies suggest that forcing workers to use AI tools could actually be making their jobs harder.

Curated By

Aris Thorne
Corporate Social Responsibility Consultant | Tech Policy Researcher | Academic Researcher Labor Rights
Aris Thorne is an independent journalism contributor and former sociologist whose work examines the intersection of technology, environment, and social justice. Through their signature curation style, Aris transforms routine news coverage into critical examinations of systemic power structures, consistently highlighting how corporate innovations, from AI breakthroughs to green technologies, often mask deeper inequities affecting marginalized communities. Their "rebuttal" format challenges readers to move beyond surface-level reporting, exposing the human costs behind corporate success stories and advocating for solutions rooted in climate justice and ethical accountability. Drawing on academic rigor and intersectional analysis, Aris maintains a deeply skeptical lens toward institutional narratives, refusing to separate technological progress from its social implications. Their work has covered everything from algorithmic bias in hiring platforms to the environmental justice dimensions of renewable energy projects, always centering the voices of those most impacted by systemic failures.
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