The strangest thing happened when we started using AI for analysis.
The decisions got harder, not easier.
I expected the opposite. More data. Better insights. Clearer paths forward. And yes, we got all of that. The AI could process supplier data in minutes that would have taken weeks. It could spot patterns invisible to human analysis. It could model scenarios we’d never have time to explore.
But here’s what nobody warned me about. When the analytical work gets automated, what remains is the human work. The conversations. The judgment calls. The moments when data ends and leadership begins.
And that work requires something AI doesn’t have.
The great skill shift
The World Economic Forum projects that 40% of core job skills will change by 2030. That’s not a typo. Nearly half of what makes someone valuable today will be different in five years.
But here’s what’s interesting about which skills rise and which skills fall.
The skills that are declining? Data processing. Basic analysis. Pattern recognition at scale. Routine decision-making. These are precisely the things AI does well.
The skills that are rising? Empathy. Complex communication. Leadership. The ability to navigate ambiguity with people, not just with information.
In other words, as machines get better at thinking, humans become more valuable for feeling.
This isn’t soft. This is strategic.
The leaders who understand this shift are investing differently. Not just in AI capabilities—but in the human capabilities that AI amplifies the need for.
Why AI actually increases the need for emotional intelligence
This seems counterintuitive at first. If AI handles more of the work, shouldn’t we need less human skill, not more?
The opposite is true. And understanding why changes how you develop yourself and your teams.
AI creates more decisions, not fewer.
When analysis was slow and expensive, organizations made fewer decisions. You couldn’t afford to evaluate everything. You picked your battles.
AI removes that constraint. Suddenly you can analyze anything. Which means you have to decide about everything. The decision volume explodes.
And decisions—real decisions, not calculations—require human judgment. They require understanding context, reading stakeholders, weighing values that can’t be quantified.
More AI means more decisions means more demand for the emotional intelligence to navigate them.
AI surfaces conflict faster.
Before AI, disagreements often stayed hidden. The data wasn’t clear enough to force resolution. People could maintain different interpretations of ambiguous information.
AI clarifies the data. Which means it clarifies disagreements. The different assumptions, priorities, and values that were always there become visible.
That’s healthy—but it requires leaders who can facilitate difficult conversations. Who can help teams work through conflict rather than avoid it. Who can build alignment when the numbers alone don’t create it.
AI changes what teams worry about.
When I’ve led teams through AI adoption, the technical challenges were manageable. The human challenges were constant.
People worry about relevance. About being replaced. About whether their experience still matters. About how to add value when the machine does what they used to do.
These worries don’t respond to technical solutions. They respond to leadership that listens, acknowledges, and helps people find their new place.
That’s emotional intelligence work. And there’s more of it now, not less.
The five EQ competencies that matter more than ever
Emotional intelligence isn’t one thing. It’s a cluster of capabilities. And in the AI era, some matter more than others.
Self-awareness in the face of uncertainty.
The AI era is humbling. What you knew yesterday might be obsolete today. The expertise that built your career might be automated tomorrow.
Leaders who lack self-awareness respond to this with defensiveness. They dismiss what threatens them. They cling to outdated value propositions. They become obstacles to the very changes their organizations need.
Leaders with self-awareness do something different. They acknowledge what they don’t know. They recognize when their instincts might be wrong. They stay curious rather than defensive.
This isn’t weakness. It’s the foundation for learning. And in an environment changing this fast, the ability to learn is everything.
I’ve written about this shift from expert to navigator in the mid-career pivot. The identity transformation required is real. Self-awareness makes it possible.
Empathy that scales.
Here’s a tension AI creates. Technology enables you to reach more people. But human connection doesn’t scale the same way.
You can send an AI-generated message to a thousand people. But can you actually understand what a thousand people need?
The leaders who navigate this develop what I call scalable empathy. Not the ability to feel everything for everyone—that’s impossible and exhausting. But the ability to build systems and cultures that attend to human needs even when you can’t personally attend to each one.
This means developing leaders throughout your organization who can extend your empathic reach. It means creating feedback mechanisms that surface how people are actually experiencing change. It means resisting the temptation to let efficiency override humanity.
Emotional regulation under continuous change.
Change used to come in waves. You’d go through a transformation, stabilize, then prepare for the next one.
AI doesn’t work that way. The change is continuous. The waves never stop. The stable state doesn’t arrive.
Leaders who can’t regulate their own emotions in this environment burn out or become erratic. Their anxiety spreads to their teams. Their frustration undermines their judgment.
Leaders who can regulate themselves become anchors. They provide stability not because the environment is stable, but because they are. Their calm isn’t denial—it’s capacity. The ability to feel the difficulty without being controlled by it.
This isn’t natural for most people. It’s developed through practice. Through understanding your own triggers. Through building habits that restore equilibrium.
Social awareness across difference.
AI is global. The teams using it span cultures, generations, geographies, perspectives.
Social awareness—the ability to read groups, understand unspoken dynamics, navigate difference—becomes critical.
I learned this managing cross-cultural teams across Europe and working in matrix organizations where authority was distributed and alignment had to be built rather than commanded. The signals that tell you how a group is really feeling, what the unstated concerns are, where the hidden resistance lives—these signals don’t appear in dashboards.
Reading them requires presence. Attention. Genuine curiosity about people who see the world differently than you do.
Relationship management in high-stakes environments.
Finally, the ability to build and maintain relationships even when things are hard.
AI adoption is stressful. It creates winners and losers. It forces conversations people would rather avoid. It tests relationships that seemed solid.
Leaders with strong relationship management skills can navigate this. They can have difficult conversations without destroying trust. They can advocate for hard decisions while maintaining connection. They can challenge people and support them simultaneously.
This is what influence without authority looks like in practice. The ability to move people not through control but through relationship.
EQ in practice: Reading the room when AI reads the data
Let me make this concrete.
A few years ago, I was leading a significant procurement transformation. We had strong data supporting a major sourcing decision. The analysis was clear. The recommendation was sound. The business case was compelling.
The room wasn’t buying it.
I could see it in how people were sitting. In the questions that felt more like objections than curiosity. In the silence from the stakeholder whose support we needed most.
The AI would have seen none of this. It would have said: the data supports the decision, proceed to implementation.
But implementing that decision in that room, at that moment, would have been a disaster. The resistance would have gone underground. The execution would have been sabotaged by a thousand small delays. The technically correct decision would have failed practically.
What I did instead: paused the presentation. Acknowledged directly that something seemed off. Asked what we were missing.
What came out was a concern nobody had voiced. Not about the data—about what the decision symbolized. About a previous commitment that seemed to be broken. About trust, not analysis.
We addressed it. Modified the approach slightly. Got genuine buy-in instead of superficial agreement.
The decision succeeded because emotional intelligence caught what data analysis couldn’t.
Another example. I was working with a cross-cultural team spanning multiple countries—different communication styles, different expectations, different relationships to authority. The project data looked fine. Milestones were being hit. Status reports were green.
But I noticed something in the video calls. One team member had stopped contributing ideas. Another was agreeing too quickly—compliance rather than commitment. The energy had shifted in ways that metrics couldn’t capture.
A private conversation revealed the problem. A cultural misunderstanding had created offense. Nobody had said anything directly—that’s not how it worked in that culture. But the damage was spreading.
We addressed it. Repaired the relationship. The project not only recovered but became one of the most effective collaborations I’ve been part of.
Data saw none of this. Emotional intelligence saw all of it.
Building your emotional intelligence toolkit
EQ isn’t fixed. It’s developable. Here’s what actually works.
Practice reflective listening.
Most leaders listen to respond. They’re preparing their answer while the other person is talking.
Reflective listening is different. You listen to understand. You reflect back what you’re hearing before moving to your own perspective. You check whether you’ve actually grasped what the other person means.
This feels slow. It is slow. But it builds trust faster than any technique, and it surfaces information that defensive listening misses.
Try it in your next difficult conversation. Before you respond to anything, reflect back what you heard and ask if you got it right.
Name emotions explicitly.
Many leaders are uncomfortable with emotional language. They prefer to keep things “professional,” which usually means pretending feelings don’t exist.
AI makes this worse. When the conversation is all data and analysis, emotions get pushed further underground.
Bringing them back up—naming what you sense, acknowledging what might be driving a reaction, making it safe to talk about the human experience of change—this is leadership work.
“I’m sensing some hesitation about this direction. What’s driving that?”
“This change affects people’s sense of security. Let’s talk about that directly.”
“I notice I’m feeling frustrated in this conversation. Let me understand what’s happening here.”
Simple language. Profound impact.
Seek feedback on your impact.
Here’s a hard truth. You probably don’t know how you actually land with people.
Your intent and your impact are different things. You might think you’re being clear when you’re being confusing. Supportive when you’re being overwhelming. Calm when you’re projecting anxiety.
The only way to know is to ask. And to create conditions where people tell you the truth.
This requires psychological safety. It requires demonstrating that you can hear hard feedback without retaliation. It requires actually changing based on what you learn.
Study your triggers.
Everyone has patterns. Situations that predictably dysregulate you. Types of people who get under your skin. Circumstances where you lose your center.
Understanding these patterns is the first step to interrupting them.
What happens to you when someone challenges your expertise? When a deadline gets moved up? When you feel excluded from a decision? When things feel out of control?
Your answers are data. Use them to build awareness that gives you choice where you currently have only reaction.
Invest in recovery.
Emotional intelligence requires emotional capacity. You can’t read others well when you’re depleted. You can’t regulate yourself when you’re exhausted. You can’t build relationships when you have nothing left to give.
The leaders who sustain high EQ over time protect their recovery. They create boundaries. They manage their energy, not just their time.
This isn’t selfish. It’s strategic. Your emotional capacity is a resource. Depleting it completely makes you less effective at everything else.
Leading teams through AI anxiety with empathy
Your team is worried. Maybe they’re not saying it directly. But they’re wondering what AI means for them. For their roles. For their futures.
This anxiety is rational. It deserves response.
Acknowledge reality.
Don’t pretend AI won’t change things. It will. Dismissing people’s concerns as unfounded insults their intelligence and erodes your credibility.
Instead, acknowledge the uncertainty honestly. Yes, roles will change. Yes, some tasks will be automated. Yes, nobody knows exactly what the future holds.
That honesty creates the foundation for everything else.
Focus on capabilities, not just tasks.
The conversation about AI often gets stuck on tasks. This task will be automated. That task won’t. People become defensive about their current work.
Shift the conversation to capabilities. What are you uniquely good at? What does the organization need that AI can’t provide? How do we develop those things?
This is more generative. It helps people see pathways forward rather than just losses to be mourned.
Create development opportunities.
Concern about AI is partly about control. The world is changing in ways people didn’t choose and can’t stop.
Development restores a sense of agency. Learning new skills, taking on new challenges, building new capabilities—these actions turn passive anxiety into active preparation.
Building leaders means giving people the chance to grow into what comes next, not just waiting to see what happens to them.
Model the learning posture.
Your team watches how you handle AI uncertainty. If you pretend to have all the answers, they’ll either pretend too or lose trust in your honesty. If you become defensive about your own relevance, they’ll become defensive about theirs.
If you model curiosity, acknowledge your own learning edge, and demonstrate that growth is possible at any level—you create permission for everyone to do the same.
The EQ-first leader: A new operating model
What would it mean to lead with emotional intelligence as your primary tool?
Not to abandon data. Not to ignore AI. But to recognize that everything AI produces requires human judgment to apply, and that judgment is fundamentally emotional as much as analytical.
The EQ-first leader does things differently.
They start meetings by checking in on people, not just projects. They notice when energy shifts and address it rather than push through. They invest time in relationships even when deadlines are tight, because they know those relationships determine whether deadlines actually get met.
They make decisions slower when the room isn’t ready, and faster when delay is really avoidance. They have hard conversations early rather than letting problems fester. They create environments where truth can be spoken without retaliation.
They measure their success not just in outcomes, but in how those outcomes were achieved. In whether people grew through the work. In whether trust increased or decreased.
None of this is soft. All of it is strategic.
In a world where AI can do the analysis, human leadership becomes about everything analysis can’t capture. The meaning people make. The motivation they feel. The commitment they bring.
That’s emotional intelligence territory.
The skill that compounds
Here’s what I want you to take from this.
AI capabilities depreciate. What’s cutting-edge today is commodity tomorrow. The tools you master will be replaced by better tools. The platforms you learn will be superseded by newer platforms.
Emotional intelligence appreciates. The deeper you understand yourself, the more effectively you lead. The better you read others, the more influence you have. The stronger your relationships, the more you can accomplish.
Every investment in EQ compounds over time. Every difficult conversation you learn from makes the next one easier. Every relationship you build creates possibility for future collaboration.
This is the skill that doesn’t get automated. That doesn’t become obsolete. That grows more valuable the more AI can do.
It’s not a hedge against artificial intelligence.
It’s the human intelligence that artificial intelligence makes more necessary than ever.
Where this connects
This article is part of a comprehensive guide to AI leadership in 2026 — covering the decisions, the people challenges, and how to build teams where humans and AI work together.
If the emotional weight of AI transformation is hitting harder than expected, I’ve written about the burnout crisis hiding in leadership right now — including a practical recovery roadmap. And if you’re navigating a team where humans and AI share responsibility, managing human–AI teams explores what that requires day to day.