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https://www.axios.com/2026/05/28/ai-spending-roi-enterprise-costs

Archive link https://web.archive.org/web/20260528114303/https://www.axios.com/2026/05/28/ai-spending-roi-enterprise-costs

Why it matters: Companies that rushed to embrace AI are now confronting ballooning IT costs, uncertain productivity gains and growing employee skepticism.

Driving the news: Microsoft canceled most of its Claude Code licenses, in part over costs, according to The Verge, and Uber's COO said AI costs are getting "harder to justify."

An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees.

Companies are citing AI's ability to automate jobs as a cause for layoffs, though Anuj Kapur, CEO of CloudBees, told Axios that workforce cuts may simply be "the only lever they can pull" to offset their AI bills.

Consumer sentiment around AI is also nosediving, and employees are rebelling against the use of the technology at work. 

What they're saying: The enterprise is undergoing a "healthy swing" away from AI overuse — or "tokenmaxxing," the push to burn as many AI tokens as possible — Ali Ansari, CEO of model training firm Micro1, told Axios.

Ansari hopes this correction will push companies toward more efficient AI use.
While the market views these tools as working equally well across the enterprise, Ansari says "the reality of AI right now is that it only works for coding."
That disconnect can drive up IT bills without leading to high return on investment in agents, he said. 

Friction point: Corporate AI adoption is running into four unique problems.

Use cases: "Most people default to automating tasks they dislike rather than tasks most valuable to the company," Sophia Velastegui, CEO of Velastegui Ventures and former chief AI officer at Microsoft told Axios. Instead, they should focus on using AI to drive revenue.

Costs: One CTO told Axios that employees were using AI models to check the weather. That gets expensive fast: Enterprise AI plans are not truly 'all you can eat,' and even simple chatbot queries can carry heavy token costs.
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[-] gayspacemarxist@hexbear.net 22 points 3 days ago

Google I get, they run the models on their own hardware. DDG makes no sense to me tho

[-] LeeeroooyJeeenkiiins@hexbear.net 10 points 3 days ago

That still costs money though so it's like why does google let me turn their search bot into a horny roleplay with a few simple "pretend you're doing this" commands while other companies charge a shitload for stuff like that and still lose money? to be clear i'm only doing the horny roleplay to lose google money, don't get the wrong idea, pervert

[-] gayspacemarxist@hexbear.net 1 points 2 days ago

Years before ChatGPT, Google was already building custom hardware for running AI workloads. The new AI companies have investments to pay off, Google has been building custom AI hardware for years now (even before ChatGPT got big). They're probably still constrained by compute, but they have much lower costs than anyone else since they already have a lot of AI-related infrastructure.

I don't really know, but I'm guessing that makes it easier to justify having a loss-leader AI product that can be used to generate training data.

[-] WalleyeWarrior@midwest.social 6 points 3 days ago

That's still resources they could have spent doing actually useful shit. Instead they are burning billions a quarter on something that is absolutely useless.

[-] gayspacemarxist@hexbear.net 1 points 2 days ago

They clearly think there's some benefit to it. Maybe all those AI queries are used for training?

this post was submitted on 28 May 2026
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