From Chief Executive Officer To Chief Everything Officer

At 7:03 a.m., the CEO wakes up. Her watch knows she is awake, the coffee machine starts, and somewhere in the cloud her AI agents have already been working for hours.

By the time she reaches the kitchen they have summarized the 47 emails that arrived overnight, flagged the eight that matter, moved two meetings, declined a third, and reminded her that the person she is having lunch with is a passionate Real Madrid supporter.

She asks what happened in her industry overnight. A competitor has launched something. Seconds later, she has an analysis.

Too long. “Give me the three things I actually need to know.”

Done.

“Now tell me why your analysis might be wrong.”

Done.

“Give me three possible responses, estimate the financial implications, and draft something I can send to the board.”

Done.

It is 7:21 a.m. She has not finished her coffee.

This scenario is exaggerated. Or maybe not?

For years we have talked about the role of the CEO, and leading business schools have built whole programs around it. The job was demanding but legible. A Chief Executive Officer set direction, allocated capital, appointed and removed people, answered to a board and a market, and understood enough finance, strategy and operations to hold the specialists to account.

Think of the classic movie executive. Miranda Priestly barely needs to finish a sentence before an organization moves around her. Someone finds the information. Someone makes the call. Someone books the table, changes the flight, assembles the materials and makes the impossible happen: a model of executive leverage we instantly recognize.

The executive decides. The organization executes.

THE JOB THAT KEEPS GROWING 

Now look at what the role has absorbed.

Today’s chief executive is expected to understand AI well enough to defend a technology strategy and increasingly have a view on whether the technology threatens humanity. To deliver for shareholders this quarter and stakeholders over a decade. To read geopolitics well enough to understand what an export control, tariff or election on another continent does to a supply chain. To be the brand, personally, on a stage and on a feed. To bridge four generations in one workforce who do not necessarily agree on what work is for. To speak on climate, inclusion and conflicts that twenty years ago might have been considered none of a company’s business.

And to make sure the numbers still land every quarter.

Nothing has been taken off the list. We only keep adding to it.

It is clear that the complexity of the role has increased. Now a technology arrives claiming it can absorb some of that complexity.

For decades technology mainly made things faster. AI is different because increasingly it does not simply give us access to information. It gives us access to capabilities.

And that changes what it means to be an executive.

We may be moving from the era of the Chief Executive Officer to the era of the Chief Everything Officer.

WHAT AI ACTUALLY CHANGES

For most of corporate history, a chief executive’s power depended heavily on the organisation around her. If she wanted to understand a new market, someone had to research it. A forecast required a modeller. A campaign required an agency. A conversation with customers in Japan required someone who spoke Japanese. Software required developers. Even a complicated week of meetings required an assistant.

Having the idea was relatively easy. Mobilizing the people, knowledge and expertise to execute it was the hard part.

Technology has been shortening that distance for decades. AI may collapse much of what remains.

An executive who cannot code can prototype software. One who does not speak Mandarin can conduct a conversation in Mandarin. One who has never built a sophisticated financial model can interrogate one. A stretched communications team can produce a first campaign without briefing an agency. Ten thousand customer comments can be analyzed without commissioning a research project.

Agents push this further still. Instead of simply answering questions or producing documents, they can take actions, interact with systems and coordinate activity.

The progression matters.

Technology gave executives better tools.
The internet gave them information.
AI gives them capabilities.
Agents give them execution.

So what happens to the expectations placed on a chief executive when the distance between “I would like this to happen” and “it has happened” begins to collapse?

THE INVISIBLE EXECUTIVE TEAM

Tomorrow’s CEO may arrive at work accompanied by an invisible executive team: a strategy agent, finance agent, communications agent, research agent, legal agent, marketing agent and dozens of specialists working simultaneously.

They do not need offices. They do not travel. They do not complain about meetings. And, rather inconveniently for the organisational chart, they can all work at the same time.

This does not mean the CFO, CMO or CHRO disappear. Organizations run on far more than task execution. They run on trust, relationships, institutional memory, motivation, politics, culture and human judgment.

They also produce something an agent stack does not necessarily produce: accident, friction and dissent.

Pixar understood this. Steve Jobs designed its headquarters to make people run into one another. Its Braintrust institutionalized candid disagreement without giving the group authority over the director. Toy Story itself was substantially reworked after an early version failed.

None of that was efficient.

That was the point.

COMMISSIONING EVERYTHING, EVALUATING NOTHING 

A chief executive surrounded only by systems that give her what she asked for should ask herself who is left to give her what she did not.

But something important changes when access to expertise is no longer determined by the number of experts sitting inside the organization.

And there is a fascinating paradox in it.

Tomorrow’s most capable executive may personally know how to do fewer things. She may not know how to code. She may be terrible at PowerPoint. She may never have built a sophisticated financial model, may not speak Japanese and may know very little about design.

Yet she can prototype the software, produce the deck, interrogate the model and communicate in Japanese.

Which creates a new failure mode for leadership:

The executive who can commission everything and evaluate nothing.

Dependency is easy to acquire and hard to notice. The harder discipline is remaining able to tell a good answer from a plausible one, to weigh what a decision does to people and not only to margin, and to retain judgment of your own while a system politely agrees with you all day.

For much of management history, executives have spent enormous amounts of time on a practical question:

How are we going to do this?

AI increasingly allows them to concentrate on a much harder one:

What should we do?

CAN AI DO THE CEO’S JOB TOO? 

But just as AI appears capable of turning the CEO into a Chief Everything Officer, another possibility emerges.

Perhaps AI can do quite a lot of what the CEO does too.

Sundar Pichai, the CEO of Google and Alphabet, made precisely this point in a BBC interview in 2025. Asked whether an AI agent might eventually be able to do his own job, Pichai replied that what a CEO does might be one of the easier things for AI to do one day.

Perhaps that should not be so surprising.

Think how much executive work consists of absorbing information, identifying patterns, comparing scenarios, allocating resources, monitoring performance and making decisions. These are precisely the activities at which AI is becoming increasingly capable.

A system with access to every financial report, customer survey, engagement score, market forecast, competitor announcement and board paper might eventually hold a more comprehensive view of an organization than any single human executive could. It does not get tired halfway through a 200-page board pack. It does not forget what the Brazilian subsidiary said three quarters ago. It does not favor one division because an old colleague happens to run it.

And it does not need to finish its coffee before looking at the numbers.

WHERE SCARCITY MOVES NEXT 

So we arrive at a strange possibility: AI could simultaneously make the CEO more powerful and more replaceable.

The more operational and analytical work AI absorbs, the more one executive can accomplish. But the more of the CEO’s own analytical and coordinating work AI can perform, the harder the question becomes:

What remains uniquely valuable about the human being in the chair?

That is the more interesting question.

If everyone can produce a polished presentation in seconds, producing it is no longer impressive. If everyone can generate a hundred strategic options, generating options is no longer difficult. If everyone has access to sophisticated analysis, more analysis does not necessarily produce better decisions.

Scarcity moves elsewhere. Judgment becomes scarce. Curiosity becomes scarce. Taste, courage and empathy become scarce. The ability to frame the right question becomes scarce, and so does the ability to recognize when an apparently brilliant answer is nonsense.

Most importantly, the ability to decide what is worth doing at all becomes scarce.

This may be the great irony of AI and leadership.

The more AI allows the CEO to do everything, the less her value can come from doing things.

Her value comes from deciding what matters.

A HARDER QUESTION FOR BUSINESS SCHOOLS 

Which raises an uncomfortable question for those of us who educate these people.

For more than a century, management education has been organized around the capabilities executives were expected to understand. We teach finance, marketing, strategy, operations, accounting and organizational behaviour so leaders know enough about each function to manage the specialists who do the work.

The MBA is the clearest expression of that logic, and so is almost every flagship senior program we sell: advanced management, general management, the CEO program, the board program. A little of every function, compressed, taught by our best people.

That was the right design for a role you could describe in a paragraph. It is the wrong design for the role as it has become.

The chief executive arriving on one of those programs does not principally need another working knowledge of marketing. She can acquire information quickly, and her agents can help produce the plan.

What she cannot acquire so easily is help with the parts of the job nobody ever taught her.

How to form a defensible view on a technology she does not fully understand. How to read a geopolitical shift she has no training to read. How to be the public face of an institution in an environment that rewards outrage. How to lead people who define work differently from her.

And how to decide, and then live with the decision.

TEACHING JUDGMENT, NOT JUST KNOWLEDGE 

None of which makes disciplinary knowledge irrelevant. Quite the opposite.

She needs finance to recognize a dangerous recommendation, strategy to challenge an attractive but flawed option, and an understanding of organizations to anticipate the human cost of a perfectly rational decision.

What changes is the purpose of that knowledge.

We are no longer teaching people primarily to produce the analysis. We are teaching them to interrogate it.

That also changes what our faculty are for.

Their value cannot come from competing with AI to supply information. It comes from something much harder: challenging assumptions, introducing ambiguity, asking uncomfortable questions, and creating situations in which someone has to choose, defend the choice, and live with the consequences.

The age of artificial intelligence may require a much more human form of management education.

The Chief Everything Officer will not need to know everything. AI makes that unnecessary and, in any case, impossible.

What tomorrow’s leaders will need is the ability to ask better questions, exercise better judgment, understand people, imagine possibilities, and decide which of the thousands of things they could do are actually worth doing.

So the question for business schools is not how we teach our students to use AI.

It is bigger than that: Are we still preparing leaders to execute in a world where execution was scarce, or to lead in a world where it is becoming abundant?

Preferably before the coffee gets cold.

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Benjamin Stévenin is the former Director of Business School Solutions and Partnerships at Times Higher Education. Leila Guerra is Associate Vice President (Education) at London School of Economics, leading the school’s lifelong learning portfolio, including Executive Education, Executive Masters, LSE Online and AI-innovations.

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