Human Development in the age of AI

Nial O'Reilly • November 9, 2026

Why AI makes leadership development more urgent, not less

When the machine does the expert work

Ask a senior leader how they got where they are, and the honest answer is often some version of: I was very good at knowing things. They knew the numbers, the market, the system, or regulation, better than the people around them. Expertise earned promotion, and the next one, and the one after that.


That route to the top is now being quietly rebuilt. The analysis that took an individual or team a week can be drafted in an afternoon. The KPIs, the market trends, the options: all of it is increasingly just a well worded prompt away. AI is very good at the thing many leaders were promoted for. That doesn’t make leaders less necessary. It changes what they’re needed for.


The expert who rose by being the expert

In our work we keep meeting a particular kind of leader. Someone brilliant, who has risen by being the best in the room at their subject, and who now leads people and problems where being the best in the room is no longer the point.


A leader I worked with recently put it plainly. Bringing a developmental framework into a culture of high-achieving experts is a specific risk, because the people in that culture have succeeded by “being the best”. Then you introduce a way of thinking that says no stage of development is better than another but some stages are better at working with complexity and better able to transform; that runs against everything that got them there.


The deficit isn’t a lack of intelligence. It’s that expertise becomes a way of seeing as well as something a person has. When your value has always come from having the answer, a question with no answer feels like a failure rather than the actual work. Finding this out can be really empowering for a senior team.


“I’m paid to have the answer”

Some years ago I worked with a senior medical professional, a professor of his discipline. Reading back what he had written during a development exercise, he stopped and said: “I can’t believe I wrote that. I can think that way at home, my wife will tell you. But at work, I’m not allowed to think that way. I’m paid to have the answer, and I’m paid to deliver it quickly. I have seen people sacked for thinking that way!”


He was capable of more complex, more open thinking, and his organisation with its very sophisticated and valuable KPI dashboard had trained him to set it aside at the door.


Now imagine that the answer, the thing he is paid to have, can increasingly be generated on demand. What is left for him to be paid for? The answer is precisely the thinking he was taught to leave at home.


Not just more skills: a bigger frame

The instinctive organisational response to AI is horizontal: train people on the tools, add a module on prompt-writing, refresh the digital competency framework. Some of that is necessary. None of it touches the real shift.


Horizontal development adds to what a person knows and can do. Vertical development changes how a person makes sense of what they know: how much complexity they can hold, how many perspectives they can keep in view at once, how they hold polarity, and how they act when the situation won’t resolve into a single right answer.


In the language of Robert Kegan this is moving from being subject to the beliefs and patterns we have “swallowed whole” to being able to hold them as object: to look at them rather than through them, and so become more choiceful and less reactive.


That is the capacity my professor had at home and couldn’t use at work. It is also the capacity AI doesn’t supply. A model can hand you more options. It cannot enlarge the frame through which you choose between them.


Why this is urgent now

For a long time, an organisation could get by with leaders who were brilliant experts and conventional thinkers. The expertise carried them.


When expertise becomes abundant and cheap, that changes. What becomes scarce is the ability to:

  • stay with a problem that has no known answer, rather than reaching for the nearest familiar one
  • hold competing views, from people and from machines, without collapsing into one of them too early
  • notice the assumptions shaping a decision, including your own
  • know when a confident answer is still only an answer


These are developmental capacities. They grow slowly, through experience, reflection and relationship. They can’t be installed like software, and they can’t be outsourced to it.


A question to carry

This series is about what AI changes for human development, and what it doesn’t. We’ll argue that AI changes what leaders need to develop, but not who does the developing.


For now, one question to take into your next leadership meeting:

If the expert answer were already on the table, free and instant, what would this team actually be for?


Next in the series: Complicated is for machines, complex is for us.

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