A year ago, Sam Altman did a striking prediction: as the production of data centers becomes automated, the cost of intelligence (AI) should at some point converge with the cost of electricity.” Or what is the same: access to AI would be very, very cheap. That has not happened by any means, but in addition to spending a lot of tokens, we are wasting them.
So much AI for what?. He phenomenon of tokenmaxxing -he rampant token consumption more like fashion than something useful—has begun to set off alarm bells, because companies have realized that they are spending small fortunes for their employees to try to get the most out of AI.
AI dismissal. A study by the startup EntelligenceAI affirms that for every dollar invested in AI, only 18 cents end up reaching production. The remaining 82% ends up being invested in correcting errors, rewriting code and executing review processes that do not generate direct value. This is what they call “unproductive spending,” and it is a warning sign because the success of this technology does not depend on us using AI non-stop, but on using it to improve productivity.
Uber warns. Andrew Macdonald, COO of Uber, I questioned openly whether this massive spending by companies like yours on AI is really justified when it is not linked to improvements in productivity. The company has been one of those that has decided to cut spending on Anthropic models because the available annual budget had already been “vented” to use them.
Investing in tokens ends up being unprofitable: the “useful part” is less than a fifth of what is invested, according to EIntelligence AI.
The uncertainty is there. Other experts They warn just the opposite: This is just the beginning of what is to come, so taking action against AI consumption may be counterproductive. The problem is not so much that AI is being used, but rather that it is being wasted: this obsession with consuming tokens caused the CFO at Amazon, for example, to tell his employees “Don’t use AI just for the sake of using it”. The company rewarded those who used AI the most, so many ended up using it for trivial, redundant or useless tasks.
Use AI appropriately. Matan Gringberg, CEO of the AI startup Factory, told in WSJ how a manager at a major financial institution had told him that his employees were spending hundreds of thousands of dollars a month on tokens. The problem was that some were using the most powerful models to answer simple questions or just to chat. The message here is clear: these models must be used appropriately to avoid wasting them: “If your daughter needs private algebra classes, you can probably find someone cheaper than Albert Einstein to give them to her,” he concluded.
We are consuming tokens beyond our means. At the Google I/O event Sundar Pichai, CEO of Alphabet, explained that the company currently processes more than 3.2 trillion tokens per month, seven times more than a year ago. Faced with this demand, both it and other companies are “punishing” the trivial use of AI models.
AI agents consume tokens like there’s no tomorrow. What has also happened is that the arrival and popularization of agentic programming tools, such as Claude Code, Codex or Antigravity, causes many more tokens to be consumed because with them it is possible to automate the execution of programming tasks (or other areas) on a continuous basis. The AI model prepares a plan, executes it, and at each step thinks and evaluates its responses before continuing with the plan. This process is intensive in token consumption, and is the main reason why token consumption has skyrocketed.
Flat rates, nothing. Monthly plans like ChatGPT Plus or Claude Pro offered leeway for developers to consume huge amounts of tokens with hardly any limitations. However, both OpenAI and Anthropic and other companies have begun to change their strategies, limiting the cases in which these flat rates can be used so that users cannot abuse them. If they want to consume more they can, but always through a pay-per-use philosophy: the more you use, the more you pay for something that at least helps users be aware that they cannot use super-powerful models for useless conversations with their chatbots.
Image | Xataka with Magnific
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