Welcome to Eye on AI. Beatrice Nolan here. In today’s issue:
Business leaders are confronting AI spending. ChatGPT’s market share falls below 50%. Top Google Gemini executive leaves for OpenAI. Americans want legal protection around AI interactions.I’m in Paris this week at one of Europe’s largest tech conferences, VivaTech, where concerns about “sovereign AI” are front and center.
The U.S. government’s move to abruptly shut down foreign access to Anthropic’s powerful Mythos-tier models last week has been a stark example of Europe’s technological dependence on America—and what happens if the U.S. decides to pull the plug. Conversations on stage and off have been focused on what AI sovereignty actually means and how Europe can achieve meaningful AI independence.
The other question on the table: AI spend. After two years of near-unrestrained experimentation, companies are starting to seriously question how much they’re spending on AI—and what they’re actually getting back.
Corporate leaders across industries are now being confronted with ballooning AI costs as employees attempt to obey directives for widespread AI adoption. Uber recently burned through its entire 2026 AI budget in four months, and its COO said AI spend is getting harder to justify. Last month, one consultant told Axios that a client burned through half a billion dollars in a single month after failing to cap AI usage for employees.
The spending reality check
Even inside companies building the technology, there’s a growing sense that the free-for-all phase might be coming to an end—at least for some customers. Peter DeSantis, SVP at Amazon, said this kind of cost shock is a normal phase of new technology adoption, with companies now moving from experimentation to figuring out how to control usage and budgets.
“Just like every technology, when we first launched the cloud, some of our most successful customers were delighted by the agility… but many of them woke up one day, and they’re like: ‘Wow, we’re spending a bunch of money,” he told Fortune. “Anytime there’s a new technology, I think there’s work to be done to figure out how to efficiently use it and how to budget for it, and I think we’re going through that.”
Buyers also say they are becoming more selective. Philippe Rambach, Schneider Electric’s chief AI officer, told Fortune the focus internally had shifted toward more deliberately matching use cases to cheaper, fit-for-purpose models.
“On the solutions that we build, we are very cautious to use the right model; you don’t always need to use the latest frontier model. Quite often you can use relatively cheap models,” he said.
“The question of the cost of AI is becoming more and more important,” he added. “We need to have that under control. We need to measure it. We need to include that in our business case, business plans, and decisions.”
In other words, not every task needs GPT-5-level or Mythos firepower, and not every employee needs access to the most cutting-edge technology. This cuts against how many companies have actually rolled AI out, with many handing out licenses liberally and encouraging heavy AI experimentation.
Recently, there’s been lots of anecdotal evidence that this pressure to “just do it” when it comes to using AI has had the perverse, but predictable, result of employees using it for almost everything—including things as trivial as checking the weather. The result is increasing costs for companies. Many businesses also still haven’t figured out where AI actually delivers meaningful ROI. As one executive told Axios, people tend to automate what they dislike, not what creates value.
Now companies are shifting from exploration to optimization—ensuring AI delivers actual business value, or at least that AI experimentation doesn’t break the bank.
Or, as Rambach put it, companies may just be “coming back to reality.”
With that, here’s more AI news.
Beatrice Nolanbeatrice.nolan@fortune.com@beafreyanolan
This story was originally featured on Fortune.com
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