It turns out that Palantir (PLTR) CEO Alex Karp’s thunderous warning about the AI industry wasn’t a one-off rant.
Over the past couple of years, the word “AI” has become like a broken record, heard at least once almost every day, often followed by a wave of anxiety.
What has happened amid all the FOMO and paranoia is that users have begun sharing virtually everything deemed “confidential” under the sun in search of answers.
Microsoft (MSFT) CEO Satya Nadella has now raised a strikingly similar concern in a recent blog post on Sn Scratchpad.
Businesses pay for intelligence, but for that to be useful, you need to present the AI model companies with proprietary data, workflows, and corrections that give them a competitive edge.
It’s actually the reverse of what Nobel Prize-winning economist Kenneth Arrow described as the information paradox.
The buyer is essentially giving up their knowledge simply to make use of what they have purchased.
Nadella’s concern is that companies ultimately pay twice, once in cash and again with institutional know-how over time.
Satya Nadella says companies may be paying for AI twice
Microsoft CEO Satya Nadella argued that the visible cost of AI might just be the beginning.
“You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful,” Nadella wrote in a recent blog post.
For AI systems to perform better, there needs to be higher-quality internal context, which likely includes employee prompts, operational procedures, agentic activity, and corrections.
More Palantir:
“Models learn ‘from exhaust,’ the prompts people write, the tools agents use, and especially the corrections people make when the model is wrong,” Nadella said. “Every correction is distilled into institutional know-how.”
Interestingly, TheStreet’s top tech contributor, Vuk Zdinjak, recently covered Palantir CEO Alex Karp’s explosive tirade against frontier-model providers.
“I am paying for tokens that create no value,” Karp said in his most recent appearance on CNBC’s “Squawk Box,” describing the frustration he hears from enterprise customers. “These people are stealing the weights and alpha of my business.”
Additionally, Karp also challenged the industry’s basic pricing model: “If I can make you $1 billion tomorrow, wouldn’t I say I’ll make you $1 billion, and I want 30%? Why are they charging for tokens if it’s so valuable?”
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Nadella’s version feels a lot less confrontational, but far more coherent, than Karp’s. Still, the underlying warning remains the same.
Businesses are effectively renting models while donating the knowledge that makes them much more capable.
“In consuming intelligence, you are creating intelligence, and what you create should belong to you,” as Nadella puts it.
Microsoft CEO Satya Nadella’s enterprise AI warning echoes concerns raised by Palantir CEO Alex Karp. Stephen Brashear/Getty Images
Nadella’s warning strengthens Palantir’s core AI pitch
For Palantir (PLTR) stock investors, Nadella’s warning is important and may have indirectly validated the problem Karp says Palantir was built to solve.
The CEO of the controversial tech firm Karp argued that enterprises should not expose their proprietary data, workflows, and operational knowledge directly to large language models outside their organizations.
Palantir’s answer is Ontology, an application layer that connects models to company operations while controlling what models can access and retain.
Karp said Ontology makes AI “safe and useful and precise,” preventing models from caching customer data, replicating the business, or transferring sensitive intellectual property.
He went a step further in his interview with podcaster Mathias Döpfner, saying businesses need an application layer that “protects your data from being essentially abused by large language model providers.”
If customers become more wary of the data they give up, Palantir could be in line for a massive long-term windfall, but it could also create valuation risks elsewhere in the AI sector.
Palantir needs to prove Ontology can turn that strategic concern into durable contracts, expanding margins, and measurable customer returns.
It’s worth mentioning that the stock is down 27% in the past six months and more than 26% year-to-date, according to Seeking Alpha data. Still, Palantir stock is changing hands at 88 times non-GAAP forward earnings, a steep premium, to say the least, compared to the sector median of around 25 times.
Nadella’s warning raises the stakes for the AI trade
The interesting part is that the broader AI trade is already up against the uncomfortable question that Wall Street hasn’t answered: Who will earn enough money to justify the extraordinary spending?
For perspective, Amazon, Microsoft, Alphabet, and Meta are projected to spend about $630 billion on data centers and AI chips in 2026 alone, according to Reuters, more than 4 times their 2023 guidance.
However, with recent developments, it seems the chickens are finally coming home to roost as the AI trade undergoes a shakeout.
Bank of America’s latest survey found that 45% of fund managers view an AI bubble as the market’s biggest tail risk, Reuters also reported. Yet investors remain heavily committed to the chip stock trade.
Moreover, several of Wall Street’s most popular personalities have sounded alarms.
Ray Dalio says AI is “now in the early stages of a bubble,” while Jeremy Grantham warns that “sooner or later, the bubble will burst.”
“Big Short” investor Michael Burry has long been skeptical of the AI boom, calling semiconductor valuations “a pure form of overvaluation” and warning that the end may be near.
Nadella’s argument adds to those vulnerabilities.
The reverse information paradox may lead customers to redirect spending toward private, model-agnostic systems, weighing on the biggest names in AI and calling their nosebleed valuations into question.
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This story was originally published by TheStreet on Jul 15, 2026, where it first appeared in the Investing section. Add TheStreet as a Preferred Source by clicking here.
