AI will commoditize management. It will make leadership a premium.
How Leadership Evolved Over 25 Years (And Why It’s About to Shift Again)
I started my career in the mid-2000s. I’ve watched leadership change a lot since then.
I was lucky — I didn’t have a command-and-conquer boss when I was starting out. But I could see that style everywhere around me. The leaders who hoarded information. Who believed their value came from knowing more than everyone else. Who led through title, not trust.
I knew that wasn’t what I wanted. And when you know what you don’t want, you do your best not to fall into those traps. So I’ve continuously tried to adapt.
Here’s the thing: leadership has always evolved. The mistake is thinking it won’t keep evolving — faster than ever.
Look at the last 25 years:
| Era | Leadership Model | What Mattered |
|---|---|---|
| ~2000 | Command & Control | “I know more than you” |
| 2000s-2010s | EQ Revolution | “I develop people” |
| 2010s | Digital Transformation | “I enable speed” |
| 2020-2024 | Crisis & Hybrid | “I lead through uncertainty” |
| 2025→ | AI-Augmented | “I orchestrate intelligence” |
Each era didn’t replace the last. It stacked. Good leaders in 2030 will still need emotional intelligence. They’ll also need new capabilities that most haven’t developed yet.
As Beth Comstock wrote in Imagine It Forward, leaders today must “move forward without having all the answers.”
That’s been true for a while. What’s different now is the pace.
Why “Wait and See” Is Now Career Suicide
In previous eras, you had a grace period. You could ignore social media for five years and still catch up. You could delay digital transformation and course-correct later.
That window is closing.
With AI, the adoption-to-obsolescence pipeline is so compressed that the “wait and see” approach is career suicide. We aren’t moving faster — the stabilization period between shifts has vanished.
Management is becoming a commodity. Leadership is becoming a luxury.
Here’s why: AI can now handle a huge portion of what “management” used to mean. Analysis. Decision-support. Scheduling. Even some people management tasks. The 2030 leader isn’t competing with that — they’re orchestrating it.
The shift is from knower to sense-maker. From “I have the answers” to “I help us figure out what the answers mean.”
And that creates a problem for a lot of “good” leaders today.
When Your Experience Becomes Your Biggest Liability
If your value is based on what you know, you’re already obsolete. If it’s based on how you think, you’re off to a good start.
AI is the ultimate pattern-matcher. It has seen more data than any human ever could. So leaders who compete on pattern recognition — “I’ve seen this before, here’s what we do” — are racing against an opponent that doesn’t sleep.
The expertise trap works like this: your previous success becomes your biggest obstacle to future relevance. Twenty years of experience can be gold, or it can be a cage. It depends on whether that experience taught you rigidity or judgment.
In her book We Need New Leaders, Charlotte Otter notes that “we have a flawed leadership archetype that mistakes confidence for competence.”
The fix isn’t abandoning expertise. It’s pairing expertise with active unlearning — the discipline to question your own pattern-matching, especially when it’s comfortable.
The death of the “subject matter expert” boss is coming. Not because expertise stops mattering, but because expertise without adaptability becomes a liability.
4 Things Leaders Will Stop Doing by 2030
Before we talk about what leaders will do in 2030, let’s be clear about what they won’t:
Be the smartest person in the room. AI has more data. Your job isn’t to out-know the machine.
Hoard information as power. Transparency wins. Information asymmetry is a relic.
Make decisions alone. AI-augmented judgment is the expectation, not the exception.
Manage through control. Distributed, trust-based models are the default. Micromanagement is a signal that you don’t belong in leadership.
The current style of leadership — top-down, autocratic, mechanistic — is failing us. But that doesn’t mean leadership is dead.
It means that leadership is going to matter more than ever.
Why Human + AI Beats AI Alone (The Centaur Model)
The good news for us is that the combination of human and AI consistently outperforms AI alone.
The best example comes from chess. After Deep Blue beat Kasparov in 1997, the assumption was that humans were done. Machines would dominate forever. But then something interesting happened.
In 2005, a freestyle chess tournament allowed any combination of players and computers. The favorites were grandmasters with powerful AI. The winners? Two amateur players using three ordinary laptops. They had developed a superior process for coaching their AI — knowing when to trust it, when to override it, and how to blend human intuition with machine calculation.
The “centaurs” — human-AI partnerships — beat both the humans and the machines. [(Link to Centaur Chess research)]
That’s why you’re not competing with AI. Your judgment, your taste — these are the key pieces of leverage you bring to a partnership with AI. The technology is a tool, one you can use to replace the tedious work or augment the work that matters.
The path you choose defines what kind of leader you become.
The 5 Roles of the 2030 Leader
So what will leaders actually do? Based on where things are heading, I see five core roles emerging:
1. AI Orchestrator
The job: Designing human-AI workflows. Knowing which tasks to delegate to AI and which require human judgment. Building teams where AI is a collaborator, not a threat.
The key question: “Where does AI accelerate us, and where does it create risk?”
The superpower: Curation — knowing which AI to invite to the table.
When Satya Nadella took over Microsoft in 2014, the company was struggling. Windows was declining. Mobile had been lost to Apple and Google. The stock had flatlined for a decade.
Nadella didn’t try to outcompete Google in search or Apple in devices. Instead, he repositioned Microsoft around cloud computing and — critically — around AI integration. He acquired LinkedIn and GitHub, and later formed an OpenAI partnership that gave Microsoft early access to GPT technology.
But here’s what made Nadella an orchestrator, not a follower: he didn’t chase AI hype. He asked which AI capabilities would multiply Microsoft’s existing strengths. Azure cloud. Enterprise software. Developer tools. He curated which AI bets to make — and which to skip.
In a world of instant AI outputs, we lose the productive friction that leads to original thinking. Part of the AI Orchestrator’s job is being a Friction Manager — intentionally slowing things down when the team is rushing toward a mediocre conclusion.
Fast isn’t always good. Sometimes the leader’s job is to create space for the thinking that AI shortcuts away.
Do this in 5 minutes: List three decisions your team makes regularly. For each one, write whether AI should lead, support, or stay out of it entirely.
2. Context Giver
The job: Turning noise into signal. When everyone has access to the same data, the leader’s job is meaning — connecting dots, providing narrative, helping teams understand why this matters.
The key question: “What does this information mean for us, right now?”
The superpower: Narrative intelligence — making data feel like a mission.
In 2012, Best Buy was supposed to die. Amazon had turned the electronics retailer into a “showroom” — customers browsed in-store, then bought online for less. The stock dropped 50%. Analysts wrote obituaries.
Then Hubert Joly became CEO. He didn’t have a retail background. He’d run a hospitality company. And his first move seemed strange: he spent a week working in a Best Buy store in Minnesota, wearing the blue shirt, talking to employees and customers.
What Joly discovered was that Best Buy’s problem wasn’t price. It was purpose. Employees didn’t know why their work mattered. Customers didn’t know why they should choose Best Buy over Amazon.
Joly’s turnaround wasn’t built on algorithms or efficiency. It was built on context. He gave employees a mission: help customers navigate the confusing world of technology. He repositioned stores as consultation centers, not warehouses. He told a story that data alone couldn’t tell.
By 2019, Best Buy’s stock had quadrupled.
In 2030, many will say human leaders are obsolete because of AI. Joly’s playbook is the answer: when everyone has the same data, the leader who provides meaning wins.
Do this in 5 minutes: Take one metric your team tracks. Write two sentences explaining why that metric matters to someone who’s never seen it before.
3. Culture Architect
The job: Intentionally designing how teams navigate change. Transformation isn’t an event — it’s the operating environment. Leaders build cultures that flex without breaking.
The key question: “How do we stay aligned when everything’s in motion?”
The superpower: Vulnerability — modeling that “not knowing” is okay.
Here’s the framework every leader needs for navigating change in the AI era.
Rick Maurer spent over 30 years studying why organizational change fails. He advised some of the world’s largest companies and identified a pattern: most leaders address only one level of resistance and wonder why people still push back.
Maurer’s Three Levels of Resistance:
Level 1: “I don’t get it.” People are confused. They don’t understand what’s happening or what’s expected of them. Fix it with clear communication, no jargon, and repeated messaging.
Level 2: “I don’t like it.” People understand, but they’re scared. They worry about their jobs, their status, their identity. Fix it with empathy, time to adjust, and showing personal benefits.
Level 3: “I don’t like you.” People don’t trust the messenger. Maybe past changes went badly. Maybe leadership has a credibility gap. Fix it with listening, transparency, and involving them in the solution.
Most leaders stop at Level 1. They explain the change clearly and assume resistance will fade. But change isn’t logical. It’s emotional.
With the World Economic Forum projecting that 39% of current skills will become obsolete by 2030, your team needs more than information. They need reassurance that they won’t be left behind.
Google’s Project Aristotle found that the best teams share one thing: psychological safety — the belief that you can take risks without being punished. [(Link to Project Aristotle / Trillion Dollar Coach)] That starts with trust. And trust starts with leaders who model vulnerability, who admit when they don’t have answers.
Culture is “a living thing that must be tended and nurtured.” The Culture Architect creates conditions where people can adapt without falling apart.
Do this in 5 minutes: Think about a recent change you led. Which level of resistance did you primarily address? Which level did you skip?
4. Judgment Layer
The job: The human checkpoint in AI-augmented decisions. Knowing when to trust the machine and when to override it. Owning outcomes regardless of what the algorithm recommended.
The key question: “What should we do — not what can we do?”
The superpower: Moral courage — overriding the “efficient” but wrong path.
AI optimizes for measurable outcomes. Leaders hold the line on things that matter but can’t be easily measured — dignity, fairness, long-term trust.
When AI recommends a decision, the leader asks: What context is the data missing? When AI flags an employee as a “flight risk,” the leader decides whether to act on that prediction. When AI drafts a communication that technically works but feels wrong, the leader kills it.
Consider Timnit Gebru, the former co-lead of Google’s Ethical AI team. In 2020, she pushed back against publishing research that downplayed risks in large language models — the same technology now powering ChatGPT and Claude. Google wanted efficiency and speed. Gebru wanted accountability.
Whether you agree with her positions or not, Gebru exemplified what the Judgment Layer means: being willing to override the “efficient” path when it conflicts with what you believe is right.
This role runs on emotional intelligence. You can’t make these judgment calls without self-awareness, empathy, and the ability to read context that data doesn’t capture.
“The algorithm recommended it” isn’t leadership. It’s abdication.
Do this in 5 minutes: Identify one decision your team made recently where AI or data provided a recommendation. Ask yourself: what did the data miss that only a human could see?
5. Human Potential Developer
The job: Coaching people for continuous reinvention. Building resilience and adaptability. Teaching people how to learn — because specific skills expire faster than ever.
The key question: “How do I help my people become AI-proof?”
The superpower: Metacognition — teaching people how to learn, not what to learn.
Liz Wiseman spent years studying what separates leaders who drain their teams from leaders who multiply them. Her research, published in Multipliers, found that the best leaders don’t try to be the smartest person in the room. They make everyone around them smarter.
Multipliers ask questions instead of giving answers. They create space for others to think. They challenge people to stretch beyond what they thought possible — and then support them when they struggle.
In 2030, the most important trait won’t be any specific skill. It will be learnability — the ability to unlearn old habits and rapidly acquire new ones as the environment shifts.
Technical skills have a half-life. The skill of learning itself doesn’t expire.
The Human Potential Developer helps people build that muscle. Not through once-a-year training programs, but through coaching that builds confidence, resilience, and adaptability every week.
“The function of leadership is to produce more leaders, not more followers.”
— Ralph Nader
Do this in 5 minutes: Think about someone on your team who’s struggling with a skill gap. Instead of recommending a course, write down three questions you could ask them that would help them figure out their own learning path.
What This Means for You Today
2030 isn’t some distant future. It’s your next strategic planning cycle.
You don’t wait until the shift is complete to start building these capabilities. You start now.
Pick one role where you’re weakest. Be honest. Is it orchestrating AI? Providing context? Building culture? Making judgment calls under pressure? Developing your people’s ability to learn?
Build a 90-day development focus around it. Read. Practice. Get feedback. Find someone who does that role well and study them.
Accept that this is ongoing. Leadership development isn’t a destination. It’s a practice of continuous reinvention.
The Hard Truth
Many “good leaders” today will struggle with this shift.
Not because they’re bad people. Not because they lack intelligence. But because their pattern-matching is too rigid, their expertise has become a cage, and they’ve stopped learning.
The leaders who win the next five years won’t be the ones who resisted change. And they won’t be the ones who outsourced their judgment to machines.
They’ll be the ones who learned to hold both — human wisdom and artificial intelligence — in productive tension.
Leadership has always evolved. The question is whether you’ll evolve with it — or get left behind.
That’s the work.
And it starts now.
What role are you focused on developing?
FAQs
A: Leaders in 2030 will need five core capabilities: AI Orchestrator (designing human-AI workflows), Context Giver (turning data into meaning), Culture Architect (leading through constant change), Judgment Layer (ethical decision-making), and Human Potential Developer (coaching adaptability). Technical expertise alone won’t be enough — the premium will be on human judgment and emotional intelligence.
A: AI will replace management tasks, not leadership. Analysis, scheduling, and decision-support can be automated. But leadership — providing meaning, building culture, making ethical judgments, and developing people — requires human capabilities that AI can’t replicate. The combination of human and AI (the “centaur” model) consistently outperforms either alone.
A: Start by identifying which of the five 2030 leadership roles is your weakest: AI Orchestrator, Context Giver, Culture Architect, Judgment Layer, or Human Potential Developer. Build a 90-day development focus around that role. Practice active unlearning — questioning your own assumptions and pattern-matching. The leaders who thrive will be those who learned to hold human wisdom and AI capability in productive tension.
Leadership has always evolved, but AI is compressing decades of change into years. The five roles of the 2030 leader — AI Orchestrator, Context Giver, Culture Architect, Judgment Layer, and Human Potential Developer — represent capabilities that most leaders haven’t developed yet. The winners won’t resist AI or outsource their judgment to it; they’ll learn to partner with it while protecting what makes leadership irreplaceably human.
