If AI Does The Work, What's The Leader For?
For three years, the AI question was about workers: Can they keep up, can they learn it, will it replace them? Now we see that the workers are fine. The bigger shift is happening one level up, to the leaders.
A Stanford study looked at which work skills are gaining and losing value as AI spreads. The skills losing value are the ones we used to pay the most for: analyzing data and processing information. The skills gaining value are human: organizing work, teaching, communicating.
And that changes a leader's role and value.
A Stanford study looked at which work skills are gaining and losing value as AI spreads. The skills losing value are the ones we used to pay the most for: analyzing data and processing information. The skills gaining value are human: organizing work, teaching, communicating.
And that changes a leader's role and value.
From Management To Design
For a long time, a leader's value came from managing people one by one. You reviewed their work. You gave direction. You helped each person get better at their craft. AI has taken over a lot of that. It drafts, analyzes, summarizes, checks. The work that used to fill a person's day and a manager's attention is now partly done by a machine.
So, the job moves up a level, from managing individuals to designing how the whole thing works.
It helps to name two different things here. There are individual capabilities: a person's skills, mindset, habits. And there are organizational capabilities: how work is designed, how decisions are made, whether people feel safe speaking up. Since the start of the AI boom, most of the effort has gone into optimizing the first category. The payoff now depends on the second. That's what Microsoft's latest "Work Trend Index Annual Report" found: The biggest factor in whether AI pays off is not individual expertise but how the organization is built.
I saw this in a governance study I co-authored: Most people understood the risks of AI well, but two-thirds had no way to raise a concern when something went wrong. They knew plenty, but the structure around them was empty.
For a long time, a leader's value came from managing people one by one. You reviewed their work. You gave direction. You helped each person get better at their craft. AI has taken over a lot of that. It drafts, analyzes, summarizes, checks. The work that used to fill a person's day and a manager's attention is now partly done by a machine.
So, the job moves up a level, from managing individuals to designing how the whole thing works.
It helps to name two different things here. There are individual capabilities: a person's skills, mindset, habits. And there are organizational capabilities: how work is designed, how decisions are made, whether people feel safe speaking up. Since the start of the AI boom, most of the effort has gone into optimizing the first category. The payoff now depends on the second. That's what Microsoft's latest "Work Trend Index Annual Report" found: The biggest factor in whether AI pays off is not individual expertise but how the organization is built.
I saw this in a governance study I co-authored: Most people understood the risks of AI well, but two-thirds had no way to raise a concern when something went wrong. They knew plenty, but the structure around them was empty.
3 Elements Of The New Leadership
That's the shape of the new job. Capable people, unbuilt systems. It shows up in three places.
1. Work Design
The old job was to get more out of each person. The new job is to decide what the freed-up time is used for.
When AI takes over part of the work, the easy move is to pour more of the same into the gap. The better move is to redesign the work itself. When I wrote my book, CLICKING, the thing that separated self-sufficient teams from ones that got lost in constant change was how they decided who owned what and how the work was structured. That mattered then. AI just raised the stakes on it.
From what I hear on my Built by People Leaders podcast, the HR leaders who do this redesign well don't fill the saved time with more of the same. They rebuild the role so it goes toward higher-value work.
2. Decisions
The old job was to be the answer. People brought you the hard call, and you made it or checked it.
That doesn't hold when AI is producing work across the whole team at once. You can't be the final read on everything. One person in that same study described a junior employee who trusted an AI tool's confident but wrong reading of a legal document. A senior colleague caught it—by luck, not by design.
The new job is to build the thing that makes good decisions happen without you. Who owns what, where a concern goes, which work gets a second set of eyes before it counts. I've written before about designing this kind of decision architecture: sorting which choices need your judgment, which need only your oversight and which run better without you.
Ideally, you stop being the answer and start being the person who builds where answers come from.
3. Psychological Safety
The old way to shape a team was informal. Set the tone, build trust, maintain good relationships. That still matters, but it's no longer enough.
I see this in my consulting work, too: People don't fully trust what AI gives them, so they check it by hand and say nothing. There's nowhere to raise the concern. Safety used to mean people could push back on each other. Now it also means they can push back on the tool and say "This looks wrong" out loud, without it reading as if they're slow or behind.
What To Do This Week
1. Don't be the answer; lead the conversation.
Heroic leadership is over. The machine has more answers than you do now. What it can't do is run the room: Get the team talking about how to redesign the work, how to make the call, where AI might be wrong. Your job isn't to know the answer anymore; it's to build the place where the team figures it out.
2. Redesign the work rather than just handing out tools.
The companies pulling ahead right now aren't the ones with the most state-of-the-art AI. They're the ones who rebuilt how the work happens around it. A new tool on top of an old job wastes both. Take the work AI changed most, and rethink what that job is for.
3. Reward judgment, not output.
A machine can produce, but it can't decide what's worth producing. That's the human part, and it's the part that matters now. Praise the person who asked whether the work was right, not the one who finished first. What you reward is what your team learns to value.
Final Thoughts
AI moved the value toward interpersonal and organizational skills. What's left to decide is whether you run the old job a little longer or start building the new one.
Follow me on X or LinkedIn. Check out my website.
This article was originally published on Forbes Coaches Council
That's the shape of the new job. Capable people, unbuilt systems. It shows up in three places.
1. Work Design
The old job was to get more out of each person. The new job is to decide what the freed-up time is used for.
When AI takes over part of the work, the easy move is to pour more of the same into the gap. The better move is to redesign the work itself. When I wrote my book, CLICKING, the thing that separated self-sufficient teams from ones that got lost in constant change was how they decided who owned what and how the work was structured. That mattered then. AI just raised the stakes on it.
From what I hear on my Built by People Leaders podcast, the HR leaders who do this redesign well don't fill the saved time with more of the same. They rebuild the role so it goes toward higher-value work.
2. Decisions
The old job was to be the answer. People brought you the hard call, and you made it or checked it.
That doesn't hold when AI is producing work across the whole team at once. You can't be the final read on everything. One person in that same study described a junior employee who trusted an AI tool's confident but wrong reading of a legal document. A senior colleague caught it—by luck, not by design.
The new job is to build the thing that makes good decisions happen without you. Who owns what, where a concern goes, which work gets a second set of eyes before it counts. I've written before about designing this kind of decision architecture: sorting which choices need your judgment, which need only your oversight and which run better without you.
Ideally, you stop being the answer and start being the person who builds where answers come from.
3. Psychological Safety
The old way to shape a team was informal. Set the tone, build trust, maintain good relationships. That still matters, but it's no longer enough.
I see this in my consulting work, too: People don't fully trust what AI gives them, so they check it by hand and say nothing. There's nowhere to raise the concern. Safety used to mean people could push back on each other. Now it also means they can push back on the tool and say "This looks wrong" out loud, without it reading as if they're slow or behind.
What To Do This Week
1. Don't be the answer; lead the conversation.
Heroic leadership is over. The machine has more answers than you do now. What it can't do is run the room: Get the team talking about how to redesign the work, how to make the call, where AI might be wrong. Your job isn't to know the answer anymore; it's to build the place where the team figures it out.
2. Redesign the work rather than just handing out tools.
The companies pulling ahead right now aren't the ones with the most state-of-the-art AI. They're the ones who rebuilt how the work happens around it. A new tool on top of an old job wastes both. Take the work AI changed most, and rethink what that job is for.
3. Reward judgment, not output.
A machine can produce, but it can't decide what's worth producing. That's the human part, and it's the part that matters now. Praise the person who asked whether the work was right, not the one who finished first. What you reward is what your team learns to value.
Final Thoughts
AI moved the value toward interpersonal and organizational skills. What's left to decide is whether you run the old job a little longer or start building the new one.
Follow me on X or LinkedIn. Check out my website.
This article was originally published on Forbes Coaches Council