Satya Nadella issues stark warning to companies using AI

Among the many debates surrounding AI's potential drawbacks, one concern has Silicon Valley AI enthusiasts particularly worried: that major AI labs selling proprietary models may be operating like Trojan horses.

The fear is that as startups and enterprises adopt AI models from labs such as OpenAI and Anthropic, those labs gain increasing access to the companies' most sensitive business data. The model makers could then use that knowledge for their own benefit, potentially turning into competitors of their own customers. Warnings about this risk come from voices ranging from VC Jason Calacanis to Palantir CEO Alex Karp.

Now, in a surprising blog post on Monday, Microsoft CEO Satya Nadella has added his voice. Nadella warns that AI users—whom he calls "buyers"—are paying twice. They knowingly pay for AI token usage, but they also unknowingly hand over valuable data in the process.

"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. The better you want the model to perform, the more of that knowledge you have to feed it!" he writes.

Most dangerously, he argues, enterprises are essentially teaching models the nuances of their own businesses.

"Models learn from 'exhaust,' the prompts people write, the tools agents use, and especially the corrections people make when the model is wrong. Every correction is distilled into institutional know-how," he writes.

This is "the kind of knowledge a competitor could never buy," yet enterprises are giving it away.

Nadella argues that if AI companies are allowed to freely scrape the internet to train their models, it's only fair that enterprises get to study—or "distill"—those models in return. "Distillation" refers to using a model's own outputs to understand how it works and train a new, often cheaper model based on those insights. In February, Anthropic accused Chinese open-source models of sending millions of prompts to Claude to improve their own models, urging the U.S. government to tighten export controls.

Nadella's point is that model makers cannot have it both ways. It is hypocritical for them to freely train on the world's data while restricting others from doing the same to their models.

"While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation," the Microsoft CEO writes.

Nadella is particularly concerned when model makers "reserve the right to learn from customer usage and interaction data."

Nadella's solution is the kind of thing a CEO of a massive cloud provider would suggest. He wants companies to "retain ownership" of their data, including prompts, feedback, and more. So he urges them to build their own "proprietary learning environments" on the cloud—where their data likely already resides anyway, and conveniently, that could mean Microsoft's cloud, Azure. He also recommends companies implement what he calls "orchestration layers"—essentially a way to easily switch between AI models from different providers rather than being locked into one. Tools like AI "gateways" that enable exactly this have become increasingly popular.

While Nadella never uses the word "open-source" as the method for retaining ownership, that is an obvious subtext. Yet there is another subtext as well.

Large companies, many of which still operate their own data centers in addition to using the cloud, are already moving toward open-source models installed on their own premises ("on-prem" in industry jargon). Idit Levine, founder and CEO of Solo.io—which makes networking and security software to help enterprises manage AI systems—says she is seeing this exact shift with her own customers. After experimenting with proprietary model makers, they start asking: "Can I take an open-source model and run it on-prem? It will do almost 90% of what the big one's doing. It will cost way less," she tells TechCrunch. "They understand that, and they can control it."

Solo.io's technology was selected last year as the tech powering the Linux Foundation's Agentgateway project. Her company counts enterprises like T-Mobile, ADP, and SAP as customers. She sees companies increasingly installing on-premise open-source models and views this as the next big wave in enterprise AI use.

She is not alone. Vercel—best known as a platform for building and hosting websites, which has recently added AI model-switching tools—and OpenRouter, a company that helps developers route requests across different AI models—are both seeing a surge in traffic to open-source models. In fact, open models accounted for 29% of all traffic routed through Vercel's gateway last month.

With the CEO of Microsoft, a company that has invested in both OpenAI and Anthropic, now openly urging enterprises to be cautious about using proprietary models, we expect this trend to continue growing. "In consuming intelligence, you are creating intelligence. And what you create should belong to you," Nadella writes.