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TL;DR A company reportedly burned through $500 million in Claude credits after forgetting to set limits for employees.
This example exposes loopholes in the promise that AI will reduce enterprise costs.
Additionally, we’re starting to see pushback from corporations and consumers about rising AI costs.
It’s been an unexpected shift in opinions on AI, with corporates recently pushing back on its use due to unsustained output despite mounting API costs. Leaders at brands such as Costco, Delta Airlines, and IBM have recently echoed their concerns about AI and a preference to retain the human workforce, especially as others, such as Amazon, Meta, and Microsoft, continue to cut jobs. Most recently, comments from Uber’s new COO, Andrew Macdonald, about AI-related costs and token usage not improving workers’ productivity as they should were heard, and mostly appreciated, across the internet. This was followed by reports that Uber engineers had already exhausted their AI budget for 2026.
Turns out Uber may not be the only company struggling to keep its AI budget in check. According to an Axios report (paywalled), an unspecified company burned through roughly $500 million in Claude credits after failing to put guardrails on usage. This, among other incidents, is starting to push corporate leaders to evaluate whether AI is truly delivering the value they first assumed.
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The report also notes that the corporate cadre is starting to ditch “tokenmaxxing,” a term used to describe the tendency to burn through AI credits as fast as possible. To counter that sentiment, AI biggies, including Google, have been building models and inference techniques that are more cost-efficient.
Adding to this, a recent Gartner report says that inference costs for generative AI models in 2030 will be only a tenth of what they were in 2025. However, it’s important to note that usage may also grow exponentially, especially as our reliance on AI agents increases and processes become more complex. The report also predicts token usage to expand anywhere from 5 to 30 times the current usage.
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