June 2, 2026
Cash me outside, AI
AI Doesn't Have ROI
The AI party hit the credit card limit and now everyone’s asking what they even paid for
TLDR: The big shock is that companies are finally seeing the real cost of AI tools, and many still can’t prove the spending actually pays off. In the comments, some say the bubble is deflating fast, while others insist AI works fine when it quietly helps real products instead of being sold as magic.
The mood in the comments is basically: the hype hangover has arrived. The article lays out a brutal reality check — big companies are struggling to prove that all this artificial intelligence spending actually makes money, and some are finding out the hard way just how fast the meter runs. One company reportedly burned $500 million in a month on Anthropic’s tools after forgetting spending limits, while GitHub Copilot users were furious after suddenly discovering a single prompt could eat huge chunks of their monthly credits. For many readers, that wasn’t just bad billing — it was the moment the magic trick stopped working.
The hottest reaction? Pure whiplash. One commenter said the corporate mood swung from “use AI all the time go!” to strict budgets and lockdowns in just six months, calling it a reversal unlike anything they’d seen in decades. But not everyone joined the doom parade. A few pushed back, saying AI can pay off when it quietly improves a product and customers pay for results, not for the shiny “AI” label. That sparked the real drama: is AI useful, or was it oversold as a miracle worker that would replace whole teams overnight?
And then came the dark comedy. One user joked that the real return on investment is replacing workers… right up until no one has money left to buy anything and the whole economy faceplants. Another summed it up even more bluntly: companies now have to pay for both the tokens and the humans they thought they could replace. Ouch.
Key Points
- •The article says recent reporting and executive comments show growing difficulty in justifying AI spending because returns are hard to link to business outcomes.
- •It cites Uber executives and Axios reporting as examples of companies confronting unexpectedly high AI costs, including a reported $500 million monthly spend on Anthropic models by one company.
- •The article argues that AI ROI is difficult to measure and that the cost of individual AI tasks is also hard to standardize or predict.
- •It highlights Microsoft GitHub Copilot’s move to token-based billing as an example of users discovering how quickly AI credits can be consumed.
- •The article contends that subsidized AI subscriptions across the industry obscure real costs, making AI services appear cheaper than their underlying usage would suggest.