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Possible · 3 min · Jun 5, 2026

Enterprises need to keep their tacit knowledge inside

Satya Nadella argues that a firm's distinct judgment and know-how can be captured in AI models—and can leak if the firm doesn't control the process. He says companies should train and improve models inside their own environment.

Satya Nadella

Satya Nadella is chairman and CEO of Microsoft.

Led Microsoft's cloud infrastructure and services transformation, and has been CEO since February 2014.

  • Reid Hoffman, Host · Co-founder, Manas AI

    Co-founded LinkedIn; one of OpenAI's first investors; Greylock partner.

About this segment

Satya Nadella argues that a firm's distinct judgment and know-how can be captured in AI models—and can leak if the firm doesn't control the process. He says companies should train and improve models inside their own environment.

From “Satya Nadella: AI Is the Future of the Firm”, Jun 5, 2026. Watch the full episode

“Your data is your context. You feed the model. You collect, in fact, these traces or trajectories of how work gets done between humans and agents inside the enterprise.”
Satya Nadellaat 9:25 · Possible9:25

Takeaways

  1. A firm's tacit knowledge is a form of intellectual property.
  2. Human work traces can encode that knowledge in models.
  3. Keep the learning loop inside systems the company controls.

In this episode

Full episode

  1. 6:55Enterprises need to keep their tacit knowledge inside3:01

  2. 31:29Match model cost and capability to the problem3:32Up next
  3. 51:27AI needs tangible benefits to earn public trust3:54
  4. 5 more moments in the full episode

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 6:59

    we need our own frontier intelligence, but we also need to maintain control of our data. Yeah, see, that I think is the question, which is this economy is going to be shaped going forward by both human capital and let's call it this token capital, right? That is true for Microsoft. That is true for a new startup. That's going to be true for any bank that's been in existence for 100 years, right? It doesn't matter.

  2. 7:25

    All of us will now need to sort of, in fact, the interplay between human capital capital and token capital and compounding the returns of it is what you need to do. So if you sort of frame it that way, then one of the most important thing is not just even thinking of data in its aggregate sense, right? See, what is the tacit knowledge of an enterprise or a firm? It's the unique ways that you are able to operate, pass judgment, have taste.

  3. 7:54

    All that's the tacit knowledge, mostly captured today in the tacit knowledge that is there with the human capital, and some artifacts that are digital. So now, when it comes to AI, the model, in some sense, is able to extract, if anything, that tacit knowledge through human trajectories and encode it in a set of weights in a model. So what I claim is that every enterprise now needs to be more mindful about that interplay of humans and their digital estate working to together, those trajectories, training essentially the models that they keep as IP versus leak it.

  4. 8:36

    Because if you leak it, it's a one-way door. You're done in some sense, right? Which is what is unique, what you may have spent a hundred years, right? In fact, we don't even know how to articulate it, right? Nobody sort of has a line item in their balance sheet called tacit knowledge. But we take it for granted that because we have human capital, we have it. Now, I believe that can leak. And in fact, it is leaking, right? If you look at even how the model companies learn, they're essentially setting up these gyms with rewards, which are employing employees who worked at your company previously. I mean, that sort of should tell you everything, what should not be happening, which is, so that's one of the fundamental reasons why we want this effectively the regime to change or the paradigm to change, where you welcome the models to come in, they should

  5. 9:26

    hill climb inside a machine that you control. Your data is your context. You feed the model. You collect, in fact, these traces or trajectories of how work gets done between humans and agents inside the enterprise. But you have a continuous loop of that and you're not letting that leak. That, I think, is the fundamental operation. Yep. And actually, the related parallel to the tacit knowledge is, and this is one of the conversations you and I had actually at the