A new word for the boardroom
This month Microsoft’s CEO, Satya Nadella, put a new phrase into the boardroom conversation: token capital. He set it out in a talk with Reid Hoffman just after Microsoft Build 2026 and in interviews since. It is worth a leader’s attention. It hands you a useful new word.
His argument is that companies now need to think about two kinds of value. The first is human capital. That is your people: what they know, who they trust, how they spot a problem before it grows. The second he calls token capital. That is the AI capability your company builds, controls and compounds for itself, the part that gets stronger the more your people use it.
He said this in the same season that Microsoft launched seven of its own AI models, built in-house. The signal is clear: Microsoft wants more of the AI under its own roof and less reliance on what it rents from others. Keep that in mind. We will come back to it.
What “token capital” actually means
Let me make this simple.
Think of someone who has worked at your company for twenty years. She knows which client hates surprises. She knows why the system always wobbles in December. She knows who to call when something breaks. None of this is written down. It lives in her head.
Now imagine you could catch that kind of know-how inside your AI, so the system gets a little better from the way your people use it. That growing know-how is your token capital.
Nadella calls the engine behind it a learning loop. It works like a circle. Your people do the work. The system captures what matters: the context, the decisions, the corrections, the way the work actually gets done. That is then used to make the next AI-assisted step a little better. Round and round it goes. Your company gets sharper with each turn.
His key point is the one to remember. You can outsource a task. But if you also outsource the learning that comes with it, you have given away more than work. You have given away future advantage.
And here is the trap most leaders miss. If you rent a general AI and let it do all the thinking, the learning piles up on the side of the company that owns the AI. Not on yours. His advice is to build the loop so the experienced know-how stays yours, even when you swap the underlying AI for a newer one.
Why a vendor is warning you about vendors
Here is the part that should make you sit up.
The warning comes from Microsoft. Microsoft is one of the handful of giants that sell these AI models in the first place. And it arrived in the same week Microsoft put its own new models on the market.
This is not a reason to roll your eyes. It is the shape of the market we are now in. The company that profits when you depend on it is also the company that can see, very clearly, how risky that dependence is. So take the insight seriously. Just do not swallow the sales pitch along with it.
And this is bigger than Microsoft. It is the new vendor problem. Every AI supplier wants to sit inside your work, your context and your learning loop. The names will change. The question will not.
Nadella reaches for history to make his case. In the first wave of globalisation, whole industries were hollowed out by outsourcing. The headline numbers looked fine. The damage underneath was real. We are still living with it. He warns that we could repeat the same mistake with AI, with a few systems soaking up everyone’s knowledge and handing nothing back. People, he says, will not accept that world for long.
And this lands hardest on the smaller players. A small company, a town council, a small island economy: none of them will ever build a giant AI model of their own. True. But that is the wrong thing to measure. You may not be able to build the engine. You can still own your loop. Do not confuse “we cannot build the model” with “we cannot own anything.”
Where the value quietly leaks
Two parts of my P-SEP model do the heavy lifting here: Security and People.
Security, first. Treat your learning loop like any crown jewel. You would never keep your cash in a safe you cannot open, or in someone else’s safe with no key of your own. Your company’s know-how deserves the same care. So ask the plain question. If we walked away from this provider tomorrow, would we keep what we have learned, or would it stay locked inside their machine? If you do not know the answer, that is your first finding.
Then People. The loop is only worth something because of human judgment. The danger here is quiet. If leaders treat AI as a cheaper stand-in for their people, they slowly empty out the very knowledge they were trying to bottle. Your veteran’s instinct is the gold. The AI carries it further. It does not invent it.
Three questions to ask before your next AI deal
You do not need to be technical to lead this well. You need three questions.
- Who owns our learning loop? If the honest answer is “our supplier,” you have work to do.
- Could we change AI providers without losing what we have learned? If not, you are not a customer. You are a tenant who can be moved out.
- What of our own knowledge is already flowing into someone else’s system? Did we choose that on purpose?
Ask these out loud in your next meeting. Watch how quiet the room gets.
Through the P-SEP lens
People. The loop is only as good as the judgment of the people feeding it, so sharpen your experts with AI instead of quietly replacing them, because the day you lose them is the day the know-how walks out of the door with them.
Security. Guard your learning loop like a crown jewel and always keep a way out, because know-how you cannot take with you was never really yours.
Ethics. Be honest with your people about what the AI learns from their work, since turning their expertise into company property while they are shown the door is a promise quietly broken.
Privacy. Know exactly what data feeds the loop and where it travels, because “we fed it everything” is not a strategy. It is a leak with a delay.
In your organisation. Name an owner for the loop, the way you would name an owner for cash or for safety. What belongs to everyone in theory belongs to no one in practice.
Basics in order. On one page, write down where your most valuable know-how lives today and who could take it away. Start there.
In plain words
Human capital. Everything your people know and can do, including the judgment that never gets written down.
Token capital. The AI capability your company builds, controls and compounds for itself, which gets stronger the more your people use it.
Learning loop. The circle where your people teach the AI by doing their work, while the AI helps them do it better, again and again.
Model weights. The settings inside an AI model that hold the patterns it learned while training. Some of your know-how can sit there. But a lot of your token capital also lives in your prompts, your feedback, your workflows, your data and the systems that connect them.
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