OpenAI CEO Sam Altman said AI spending has become a "huge issue" for companies. Speaking during an enterprise event this week, Altman made reference to conversation about companies scaling back their spending on AI tokens.
He claimed that the issue has gone to dominating the conversation suddenly, noting that it "never came up" at the beginning of the year. "People were totally happy with the amount they were spending," he said, claiming that they are now a "huge issue."
Some of the country's biggest companies have begun rationing access to AI tools, track usage more aggressively, and steer employees toward cheaper tools as costs rise faster than expected.
The pressure point is the token, the basic unit used to measure AI computing. Every prompt consumes tokens. As companies rushed to prove they were AI-ready, usage exploded. So did the bills. According to a Wall Street Journal report, some companies have burned through annual AI budgets in just a few months, while others have seen costs double or triple.
Executives at companies including Uber, Meta, Microsoft, Salesforce, and DoorDash have either discussed or implemented new controls aimed at making sure AI spending produces measurable gains, not just activity.
An Uber executive told the Journal that the company had already exhausted its annual budget for "agentic" AI use by March. Microsoft limited access to Anthropic's Claude Code program for some employees, directing them instead toward an internal coding assistant. Salesforce has introduced a system to connect token use to business outcomes.
Meta Chief Technology Officer Andrew Bosworth was blunt in an April memo cited by the report. "It has been great to let people experiment, but now we have too many overlapping tools," Bosworth wrote. "Nobody should be using AI tools just for the sake of using them. All motion is not progress, and token usage alone is not a measure of impact of any kind."
The problem has a nickname inside the industry: "tokenmaxxing." It refers to employees using as much AI computing as possible, sometimes because they believe heavy usage signals innovation. But expensive premium models are often used for simple tasks that cheaper systems could handle.
Matan Grinberg, chief executive of coding automator Factory, put it simply: "If your daughter needs tutoring in algebra, you can probably find someone cheaper than Albert Einstein." That realization is pushing companies to triage AI use.
Others are building homegrown tools to reduce dependence on outside providers. Anthropic, OpenAI, and Google all offer lower-cost versions of their flagship models, but some corporate buyers remain cautious about using the cheapest available systems, particularly when they come from Chinese developers.
