Of all the debates out there about the potential downsides of AI, there is one concern that is causing the most concern among AI enthusiasts in Silicon Valley. Their fear is that the giant artificial intelligence labs that sell proprietary models are somehow acting as Trojan horses.

The concern is that as startups and enterprises use AI models from labs like OpenAI and Anthropic, the labs are gaining increasing access to those companies’ most sensitive business information. Model makers can then use that knowledge for themselves, potentially becoming competitors to their own customers. Those issuing such warnings range from venture capitalists like Jason Calacanis to Palantir CEO Alex Karp.

Now, in a surprising blog post published on Monday, Microsoft CEO Satya Nadella has joined this crowd. Nadella warns that AI users (the “buyers,” as he calls them) are paying twice as much. They knowingly spend on AI tokens but inadvertently also hand over valuable data in the process.

“Basically, you pay for intelligence twice, once with money and once with something even more valuable: the unique knowledge that must be revealed for that intelligence to be useful. The better you want the model to work, the more knowledge you will have to feed it!” he writes.

The most dangerous thing is that companies are literally teaching models the nuances of their businesses, he argues.

“Models learn from ‘exhaustion,’ from the prompts people write, from the tools agents use, and especially from the corrections people make when the model is incorrect. Each correction is distilled into institutional knowledge,” he writes.

This is “the kind of knowledge a competitor could never buy,” and yet companies are giving it away.

Nadella argues that if AI companies can freely access the Internet to train their models, it is only fair that companies can study – or “distill” – those models in return. “Distillation” is the practice of using a model’s own results to learn how it works and training a new, often cheaper, model based on that knowledge. In February, Anthropic accused Chinese open source models of sending millions of messages to Claude as a way to improve their own models and urged the US government to crack down on export controls.

Nadella’s point is that model makers can’t have it both ways. It is hypocritical of them to train freely on the world’s data while restricting others from doing the same with their models.

“While the great innovation that comes from model providers having fair use rights to train models with public data is needed, I find it ironic that the status quo then turns around and imposes restrictive terms on distillation,” Nadella writes.

Nadella is especially concerned that model makers “reserve the right to learn from customer interaction and usage data.”

Nadella’s solution is the kind of thing the CEO of a giant cloud provider would suggest. It wants companies to “retain ownership” of their data, including directions, comments, etc. That’s why he urges them to build their own “proprietary learning environments” in the cloud (where their data is probably already stored anyway and, conveniently, could mean Microsoft’s cloud, Azure). He also wants companies to incorporate what he calls “orchestration layers,” essentially a way to easily switch between AI models from different vendors rather than being locked into one. Tools like AI “gateways” that allow companies to do exactly this have become increasingly popular.

While Nadella never uses the words “open source” as a method of preserving ownership, this is an obvious subtext. However, there is another subtext.

Large enterprises, many of which still have some of their own data centers in addition to using the cloud, are already moving to on-prem, open source models in industry parlance. Idit Levine, founder and CEO of Solo.io, which makes networking and security software that helps companies manage AI systems, says she’s seeing exactly this shift with her own clients. After experimenting with proprietary model makers, they’re starting to ask themselves, “Can I take an open source model and run it locally? It’ll do almost 90% of what the big guy does. It’ll cost a lot less,” he tells TechCrunch. “They understand that and they can control it.”

Solo.io’s technology was selected last year to be the technology powering the Linux Foundation’s Agentgateway project. His company counts companies such as T-Mobile, ADP and SAP among its clients. She sees companies installing more and more on-premises open source models and sees it 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 recently added AI model switching tools) and OpenRouter (a company that helps developers route requests through different AI models) are seeing an increase in traffic to open source models. In fact, open models accounted for 29% of all traffic driven through the Vercel portal last month.

With the CEO of Microsoft, a company that has invested in both OpenAI and Anthropic, openly urging companies to be careful about using proprietary models, we’re betting this trend continues to grow. “By consuming intelligence, you are creating intelligence. And what you create should belong to you,” Nadella writes.