Is the tokenmaxxing era over?

For a growing number of businesses, less is more when it comes to internal AI use.

Companies are reassessing previous decisions to equate higher AI usage with productivity, a move known more commonly as “tokenmaxxing.”

Latest example. Earlier this month, Walmart reportedly put caps on internal AI use after previously allowing employees access to unlimited tokens, as reported by Bloomberg. During a press briefing at Associates Week 2026, Walmart Global CTO and Chief Development Officer Suresh Kumar said the decision came after usage of Code Puppy, the company’s vibe coding platform, “skyrocketed,” adding that the retailer wants to get the “maximum benefits” from AI in its signature low-cost fashion.

“This is now an opportunity for us to take a step back and start saying, ‘Hey, if you are doing the same thing again and again, you don’t need to keep asking Code Puppy the exact same question again.’”

Good riddance! There are several reasons why companies are parting ways with tokenmaxxing. Drew Thompson, global lead for training and enablement at UltraViolet Cyber, told IT Brew the “short-lived trend” can be good for driving adoption of AI tools within a company, but that an employee’s AI use isn’t a good metric to rely on in the long run, and can result in hefty bills for organizations.

“Trying to get people to just maximize token usage is a lot like measuring developers on lines of code,” Thompson said. “You end up with people sometimes gaming the system or just lines of code that don’t need to be there, and same thing for tokenmaxxing.”

End of an era? Walmart isn’t the only company seemingly encouraging employees to pump the brakes on frivolous AI use. Both Meta and Amazon have reportedly pulled the plug on internal leaderboards that tracked AI token usage.

Executives have also been vocal about the lack of return on investment associated with tokenmaxxing. Uber COO Andrew Macdonald, for instance, said during a podcast interview that higher AI token usage doesn’t automatically translate into more helpful consumer features.

“That link is not there yet,” Macdonald said. “Maybe implicitly there is 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 25% more useful consumer features.’”

What’s next? Now that the tokenmaxxing party is over, where do companies go from here? Instead of just expecting employees to maximize their AI use, Thompson predicts companies will likely prioritize token spend where AI is generating value (also known as “valuemaxxing”).

“That’s where folks are going to start focusing…not on the number of tokens consumed, but, what are we getting for that usage” he said. He added that companies may allocate token budgets based on “expected demand” from workers, and allow for exceptions for highly productive employees.

“That’s perfectly fine,” Thompson added. “You probably want to bump up their budget.”

Companies distancing themselves from a culture of tokenmaxxing that still want to bolster AI use and literacy across their organizations should prioritize employee education. “Training is one of those really important activities that helps get the message out to the organization,” Thompson said. “You can really shift culture by the types of training that you provide to your employees.”