Companies Crack Down on AI Token Spending

The era of tokenmaxxing is over. After the AI industry encouraged companies to max out their AI budgets earlier this year, and some companies even built employee leaderboards to encourage internal AI usage — they are now realizing just how easy it is to spend huge sums of money on AI and get little in return. We now appear to be entering the era of token rationing.

Recent news has been rife with stories about AI cutbacks and now 404 Media reports that consulting firm Accenture has been attempting to stop its employees from depleting its token reserves by using AI to do basic tasks — like converting PDFs into presentation slides. The cutbacks take place not long after Accenture threatened that employees would “risk losing out on promotions” if they didn’t use AI, 404 writes. 404’s reporting is based on leaked audio from a recent internal meeting involving Accenture’s agentic AI strategy lead, Justice Kwak.

“We’re hitting this inflection point where AI is becoming material to the cost structure,” Kwak says. “Spend is becoming very unpredictable; and leadership, especially at the CFO, COO, and CIO level, are still asking the question of whether they’re getting value from what we’re spending on in the context of AI.” The cost of tokens has thrown into doubt the AI business model — as evidenced by what’s being called the “ AI selloff ” which has battered some AI-dependent businesses the last few days, especially memory chip makers. The AI industry has reached the stage where it can’t just be exciting and new anymore.

It has to prove its worth. Why this matters: The shift from tokenmaxxing to token rationing reflects a broader industry reckoning on the true value of AI. As companies like Accenture clamp down on spending, developers and businesses must reassess their AI strategies to ensure a strong return on investment.

For consumers, this may mean delayed or scaled-back AI-powered services. The AI industry's growth will depend on its ability to deliver tangible benefits, not just flashy demos. Open questions remain about which AI applications will prove most valuable and how companies will balance innovation with cost control.

Effective AI adoption will require a nuanced understanding of where and how to apply these technologies to drive real business value.