In theory, using an AI model to churn out a bunch of code for your software company sounds like an awesome idea. A ruthless boss can cut down their workforce and save on paying their salaries and healthcare. Or they can keep the employees, and force them to crank out even more code with an AI. Either way, it’s an efficient cost-cutting dream.
But reality is beginning to set in. Businesses are racking up huge AI usage bills they didn’t expect, with a single employee spending over $150,000 a month on AI tokens. And AI companies are feeling the squeeze that the rampant use of their coding tools is putting on their servers, causing them to jack up usage rates.
In other words, the economics of rapidly deploying AI coding tools across companies are looking more questionable than ever. And one telling weather vane of where things are headed comes from Anthropic, which quietly doubled its estimate for how much the average business will end up spending on its Claude Code tool.
The sneaky update was first spotted by Ed Zitron, who extensively covers the AI industry. Before April 16, the Claude Code document estimated the average cost per developer to be $6 per day, and the average cost for 90 percent of users to be below $12.
But the documents now state that the “average cost is around $13 per developer per active day and $150-250 per developer per month, with costs remaining below $30 per active day for 90 percent of users.”
A difference of several dollars doesn’t sound like much in isolation. But costs are clearly trending upwards, and those dollars add up. Many developers run multiple AI agents per employee at the same time, using them to churn out code for different tasks for hours on end. For organizations with thousands of employees all running their own posses of AI servants, the costs could be exorbitant — are exorbitant, in fact. Some, by their own admission, could be paying human salaries for what they’re spending on coding tools. Bryan Catanzaro, vice president of applied deep learning at Nvidia, recently told Axios that for his team, the “cost of compute is far beyond the costs of the employees.”
These questions are swirling amid AI companies doing some severe belt-tightening, cutting off free trials and limiting access to their coding models to even paid users, as Anthropic experimented with doing. This week, Microsoft’s GitHub Copilot said it would transition to usage-based billing, effectively forcing users to pay more for the code they crank out.
Meanwhile, a growing body of research has poked holes in the premise that integrating AI leads to actual productivity gains, such as an MIT study that found that the overwhelming majority of companies saw zero growth in revenue after adopting AI. Another study found that was creating a new office paradigm of “workslop,” in which AI appears to be generating more work that in reality needs to be fixed by employees down the line, both bogging down workflows and breeding resentment. Yet more studies have shown that AI is actually intensifying work for employees and driving them towards burnout.
As the costs of using AI rise, in other words, the question of whether AI is worth all the baggage it brings will be harder and harder to ignore.
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