Why Big Tech is tokenmaxxed out

**Rachel Varghese** (0:01)
AI skeptics everywhere are having a major I told you so moment. Over the last couple of weeks, we've been seeing how one of the biggest trends in AI adoption is backfiring badly, generating big bills for big tech. The trend I'm talking about and what you must have already heard of is token maxing. Just a few weeks ago, it seemed like it was the thing to be doing inside many tech companies. The basic idea was that to track real innovation and productivity, one could track an employee's token usage. Tokens, by the way, are the units of data that AI models process. While different companies measure tokens differently, it's generally considered to be equivalent to about a word and a half in the English language text. All the famous tech companies like Meta, Amazon, OpenAI and others had even set up formal or informal leaderboards to record token usage. They were even encouraging engineers and developers to compete with each other, to see who could use the most tokens. But all of that has started falling apart. Just last Friday, Amazon announced that it was scraping its internal leaderboard called KiroRank. Financial Times reported that employees were trying to boost their scores artificially through unnecessary activity, and that was driving up Amazon's compute costs. Even Microsoft has cancelled most of its internal cloud code licenses in its Experiences and Devices division. This move is supposed to be effective from June 30th, 2026 onwards. The reason is pretty much the same. The token-based billing system consumed the company's annual AI budget far ahead of schedule, and so the company is redirecting its engineers to its own AI coding assistant called GitHub Copilot CLI.
Now, the billions worth of spend on AI, specifically about $725 billion, is based on a promise. That number, by the way, is the combined amount that Amazon, Microsoft, Google, and Meta are all spending just this year on AI infrastructure. Things like data centers, chips, compute power, and the promise, the very large bet on the table, is that AI will be so productive, so transformative, that the returns will justify the cause. That AI will eventually be cheaper and faster and better than human labor. But this month, at least three companies have shown us whether that bet is paying off. And the answer, if we're being direct, is no one is sure yet.
Welcome to Daybreak, a business podcast from The Ken. I'm your host, Rachel Varghese, and every day of the week, my co-host Snigdha Sharma and I will bring you one new story that is worth understanding and worth your time. Today is Friday, the 5th of June.
Now, Amazon's official claim is that the leaderboard was not a formal one. The company had reportedly also told its employees that AI token statistics would not be tied to performance evaluations. But that did not stop employees from believing that managers were still monitoring the data. A current employee told Financial Times Mint last month that he believes the managers who track the numbers are creating perverse incentives causing some people to be very competitive about the usage. One employee even admitted to 404 Media that they cheated their way up the leaderboard after they were told in a performance review that they're not using AI enough at work. Another claim that the pressure to use AI tools was just so much and was the reason why several employees were using AI agents to maximize their token usage. Dave Dreadwell, a senior vice president at the company, maintained that while the leaderboard had been built with good intentions, the token maxing was costing Amazon. He reportedly told staff, please don't use AI just for the sake of using AI. Now, Amazon is not the only company to have suffered through this kind of an arc. In April this year, Praveen Nepali Naga, the CTO of Uber, confirmed that Uber had burned through its AI budget for an entire year in just four months. And guess what? This was apparently after the company encouraged staff to use AI as much as possible. The information also reported that the company even had a similar leaderboard that was tracking internal usage. Just this week though, Bloomberg reported that the company now has a spending limit per employee, $1,500 per month per tool. And not just that, Andrew McDonald, the company COO, expressed some doubt in the more AI use means more productivity hype in a recent podcast. He said, and I'm quoting here, Maybe implicitly there's more that is getting shipped. But it's very hard to draw a line between one of those stats and say, okay, now we're actually producing like 25% more useful consumer features. Just imagine, this is a COO of a company that blew through a year's budget in four months, is forced to set a spending limit on its employees, and now he's still struggling to justify the cost.