If AI Manages, What’s Left for Managers?

As AI automates core managerial tasks, HEC Professor Julien Jourdan explores what remains uniquely human in leadership.
 

When asked how Google uses artificial intelligence for management, Sergey Brin, co-founder of Google and head of Gemini, didn’t hesitate. “Management”, he said, “is probably the easiest thing to do with AI.”

It’s a bold claim, one that lands somewhere between provocation and prophecy. A few years ago, such a statement might have belonged in a science-fiction film. Today, it sounds almost plausible. AI copilots draft strategies, generate reports, and summarize team performance. In many companies, three out of four employees already use AI tools in their daily work (McKinsey, 2025).

So if technology can handle the humdrum routines of management, what’s left for managers to do?

At the last HEC Executive Education Day, Professor Julien Jourdan invited executives to pause and reflect on this very question. His goal wasn’t to predict when (or if) AI will take over the manager’s desk, but to help leaders think more clearly about what cannot – and probably shouldn’t – be automated: the creative, social, and ethical dimensions that still define effective leadership.

Key findings 

●    AI extends automation to cognitive management tasks, but not all are equal.
●    Tasks rich in creative and social intelligence remain resilient and human.
●    Managers must evolve toward leadership: vision, ethics, culture, inspiration.
●    Organizations that nurture these human capabilities will outlast the automation wave.

AI and the Expanding Domain of What Can Be Automated

For decades, automation has followed a predictable pattern: as computing costs dropped, machines took over routine, well-defined tasks. “In the 1970s and 1980s”, Julien Jourdan reminded the audience, “whole departments that used to process data manually simply disappeared. Tasks were automated by advances in computing.”

That first wave targeted what was easiest to codify: data entry, accounting, logistics. The new wave of AI, powered by machine learning and generative models, extends far deeper into cognitive work. It now tackles tasks that involve analysis, writing, and decision support… Areas once thought safely human.

Yet, as Jourdan emphasized, this doesn’t mean the end of jobs. 

When we look at history, the automation of tasks does not mean the disappearance of professions. Certain jobs evolve, they don’t vanish, their nature changes.

Automation affects tasks, not roles. A finance professional no longer inputs data; they interpret it. An HR manager no longer screens résumés manually; they design better interviews. What changes is the mix of tasks inside each role.

Still, there are limits, what researchers call engineering bottlenecks: barriers that slow or prevent full automation :

1.    Creative intelligence: the ability to generate and, crucially, select original ideas with value and relevance.
2.    Social intelligence: the ability to read context, emotion, and unspoken norms in human interaction.
3.    Physical interaction: perception and manipulation of the physical world.

For leadership and management, it’s the first two that matter most. Machines are excellent at producing options, but still weak at judging which ones carry meaning.

Jourdan offered a simple metaphor: “If I ask an AI to ‘draw me a sheep,’ it will produce thousands of beautiful sheep. But it won’t know which one is the right one, the one that fits the intent behind my request.”

Just like Saint-Exupéry’s Little Prince, who smiles only when shown the sketch of a box - because he can imagine the sheep within - true creativity lies in discernment.

In other words, AI can generate, but it cannot discern. And discernment, whether in strategy, people management, or culture, is the essence of good leadership.

Tasks charged with creative and social intelligence: inspiring teams, developing talent, building trust, navigating ethical choices… remain resistant to automation. More than that, they are becoming the core of managerial value in the age of AI.

The Manager vs. The Leader: Two Roles, One Person

Before asking what AI might replace, leaders must first clarify what management really is, and what it isn’t.

As Professor Julien Jourdan reminded the audience, the distinction is not new. Decades ago, researchers like Abraham Zaleznik (1977) and John Kotter (1990) drew a clear line between two complementary roles often embodied by the same person :

●    Managers seek order. They plan, organize, control, and ensure processes run smoothly. Their mission is to maintain stability and reduce complexity — to keep things running as they should.

●    Leaders, by contrast, seek change. They articulate a vision, give meaning to collective action, and mobilize people toward transformation. Their power lies not in structure, but in inspiration.

As Jourdan summarized: “The manager brings order; the leader brings movement.” The balance between the two shifts with context. Jourdan quoted John Kotter’s famous analogy to make the point:

In peacetime, an army can survive on good administration and management at every level. But in wartime, it needs competent leadership everywhere.

When markets, technologies, and expectations are stable, management dominates and processes matter most. But when the environment changes fast, leadership becomes indispensable.

And here lies the inflection point. If AI systems can increasingly maintain order (optimize budgets, monitor performance, ensure compliance) then the uniquely human edge moves to the other side of the equation: creating change.

What Tasks Are (and Aren’t) Automatable

When we look closely at how AI interacts with management work, a clear pattern emerges: not all managerial tasks are created equal.

Some functions lend themselves naturally to automation. Tasks such as performance monitoring, planning, financial and risk analysis, compliance checks, and process optimization follow structured rules and rely on large volumes of data – a perfect playground for algorithms. These are the activities where AI already delivers visible efficiency gains, reducing the time managers spend on coordination and control.

But the picture shifts dramatically when it comes to work that draws on human connection and judgment. People development, vision setting, ethical decision-making, cultural stewardship, and stakeholder relations are grounded in creativity and social intelligence – two areas where machines still struggle.

As Professor Julien Jourdan noted during his talk, AI may help generate ideas or simulate conversations, “but knowing which idea matters, or how to make it resonate with people: that’s still a profoundly human skill.”

In other words, tasks with high creative and social content remain more resilient. Even when AI supports them, it rarely replaces the human judgment they require. A system can suggest whom to promote, but it cannot sense potential; it can draft a message, but it cannot gauge how it will land emotionally.

So rather than thinking of automation as substitution, it’s more accurate to see it as reconfiguration. AI will likely absorb the management side of management (the work of planning, tracking, and optimizing) while elevating the importance of the leadership side: inspiring, guiding, and connecting people through change.

As Jourdan put it, “Technology can handle order; only humans can create meaning.”

From Management to Leadership: The New Human Frontier

As AI systems take over the analytical and procedural core of management, the center of human value is shifting. What remains, and grows in importance, are the deeply human functions that no algorithm can credibly replicate.

In Professor Julien Jourdan’s words, “It’s hard to imagine AI inspiring people or giving a team purpose.” Leadership in the age of AI, he argued, will depend less on managing output and more on animating meaning, helping teams understand why their work matters and where they are heading together.

Three domains stand out as the new frontier for human managers:

1.    Creating meaning and collective direction. Translating strategy into shared purpose and uniting people around it.

2.    Inspiring and mobilizing teams. Generating energy, not just efficiency; fostering trust and motivation through connection.

3.    Managing ethical decisions, emotions, and culture. Navigating moral ambiguity, empathy, and the unwritten norms that shape how people actually behave.

Each of these domains depends on what AI still lacks: contextual judgment, emotional resonance, and moral imagination. As Jourdan reminded, “Leadership is a profoundly social process. Transformation requires creative and social intelligence in equal measure.”

This raises a question for organizations everywhere: if AI can manage the systems, will tomorrow’s managers look more like today’s leaders? In that case, leadership will no longer be a rarefied quality reserved for the top, it will become the essential skill at every level of management.

Implications for Organizations

For executives and HR leaders, the message is clear: as AI absorbs routine managerial work, the value equation of leadership is shifting. The challenge is not to replace managers, but to rebuild how we select, develop, and support them.

First, organizations will need to rebalance their leadership pipelines toward creative and social intelligence: the abilities to imagine, connect, and mobilize. As Professor Julien Jourdan noted, the tasks most resistant to automation “depend on creative and social intelligence in equal measure.” Future-ready managers will need both.

That shift requires rethinking recruitment and succession criteria. Instead of rewarding only operational mastery, companies should elevate attributes such as curiosity, empathy, ethical reasoning, and influence across boundaries. These are the human skills that sustain culture and drive transformation.

Learning and development must also evolve. Training investments should pivot toward strategic thinking, emotional intelligence, and cross-functional collaboration. Managers will increasingly lead alongside machines: interpreting data, framing meaning, and turning insights into action. Jourdan urged caution against technological determinism: “We may overestimate the speed of this transition, but not its depth.”

In practice, most organizations will operate under hybrid management models, where AI handles operations – forecasting, scheduling, performance tracking – while humans lead transformation, ensuring coherence, ethics, and engagement.

Less Management, More Leadership

The real question is no longer whether AI will manage, but what we want human managers to focus on.
As algorithms take over the predictable, the enduring value of managers will lie in what only humans can do: give meaning, mobilize collective energy, and build trust. These are not “soft skills”; they’re the new hard edge of leadership in an AI-driven world.

That shift demands more than empathy or intuition — it calls for adaptive intelligence: the ability to read complex situations, stay lucid under pressure, and adjust one’s posture without losing coherence. This is exactly what the Adaptive Leadership in Complex Situations program, led by Professors Julien Jourdan and Emmanuel Coblence, helps participants develop.

Rather than teaching another model of management, it invites leaders to experiment with their own reflexes, to balance clarity with flexibility, and to lead through paradox instead of trying to resolve it. In practice, it’s about learning to manage the one variable AI never will: the human element.

Because when technology manages the systems, leadership begins where certainty ends.