Nurturing Leadership in the Age of AI: A Letter to Those Who Run Our Universities

Let me begin with a confession. A few months ago, standing before a hall of bright, restless management students, I asked a question I already knew the answer to. How many of you used an AI tool to prepare for today? Nearly every hand went up. Then I asked a second question, and the room went quiet. How many of you could explain why your answer was right, and defend it if I pushed back hard? Far fewer hands. Some looked at the floor.

That silence has stayed with me. It is the sound of the real challenge facing Indian higher education, and it has very little to do with technology.

I want to write to you plainly, as one educator to another. Not with a forecast about the future of work, of which there are already too many, but with a question about our own purpose. When a machine can do, in eleven seconds, much of what we have spent decades teaching young people to do, what exactly are we for?

It is an uncomfortable question. It deserves an honest answer. And I believe the answer, once we find the courage to face it, is the most hopeful thing I can offer you.

The ground is moving faster than the syllabus

You do not need me to tell you that India graduates an extraordinary number of management students every year. What is harder to absorb is how quickly the world those graduates are walking into has changed.

Look at the IT services sector, which has absorbed so many of our graduates for a generation. In a single financial year, TCS trained 350,000 of its people on AI. Wipro trained 220,000. By early 2026, Infosys, TCS, and Wipro together had put generative AI tools into the hands of more than 300,000 employees. These are not pilot projects. This is the floor of the building shifting. One industry analysis summed up the message to the workforce in four words: reskill or risk redundancy.

The Nasscom-Deloitte study tells us India needs its AI talent pool to nearly double, from around 650,000 to over 1.25 million, by 2027, and that demand is outrunning supply even as we sprint to catch up. The government has put real money behind the IndiaAI Mission, more than a billion dollars, funding research, computing power, and the training of hundreds of doctoral scholars.

And the students arriving at our gates a few years from now will be different again. Under the National Education Policy, AI and computational thinking are being woven into school education, with a structured curriculum reaching down to Grade 3 from 2026. The cohort that walks into your institution in five years will have grown up with these tools the way my generation grew up with the bicycle. Ordinary. Assumed. Always there.

Here is the trap, and I think we must name it honestly. We are rushing to teach our students how to use AI at the precise moment AI is becoming better than them at the technical work we used to certify. If our whole offer to a young person is technical instruction, then we are quietly training them to race the one opponent they cannot beat. That is not a strategy. It is a slow surrender.

What the best schools in the world quietly understood

When I look at how the world's leading business schools have responded, what strikes me is not their speed. It is their judgment about what to emphasise.

Wharton launched a full MBA major in Artificial Intelligence for Business in 2025. You might expect such a programme to be wall-to-wall code and algorithms. It is not. Wharton built it with what the school itself calls equally serious attention to ethics, governance, organisational adoption, and human behaviour. Harvard Business School has made an AI course part of its core requirement. Stanford has folded AI assistants into how students learn, while keeping a hard focus on the ethics of innovation.

Our own institutions have not been idle. The Indian School of Business runs a Leadership with AI programme that deliberately teaches strategy and governance alongside the technology, not after it. IIM Calcutta has built an advanced programme in AI for leaders. IIM Lucknow has gone so far as to theme an entire management conference around reimagining education for this era. These are good and serious efforts.

But I want to be careful here, because there is a difference that matters. Executive programmes teach working professionals who already have judgment, scars, and self-knowledge. The harder, more sacred task is what happens in the core degree, in those formative years when a young person is still deciding what kind of leader, and what kind of human being, they intend to become. That is where the real work lies. That is where we cannot afford to get it wrong.

The cruel irony hidden in the data

There is one research finding I cannot stop thinking about, and I suspect it will keep you awake too once you have sat with it.

Stanford's Institute for Human-Centered AI, in its 2025 index, described a coming shift in the economics of skill. The information-processing abilities that once earned high salaries will fall in value as AI masters data analysis. What will rise in value, and become the new premium, are the interpersonal abilities — communication, emotional intelligence, the capacity to teach and connect.

Now read that as someone who sits on a curriculum committee. The skills we find easiest to examine, easiest to standardise, easiest to put a number against — the structured analysis, the computation, the neat problem set — these are the very skills losing their market value. And the skills we have always found hardest to assess, and have therefore quietly pushed to the margins — the ability to listen, to persuade, to lead another human being, to make a hard call and own it — these are the ones the world is about to pay a premium for.

We have, in other words, spent years optimising for the wrong things. Not wrong for the world we trained in. Wrong for the world our students are about to inherit. That is a hard sentence to write, because I include myself in it.

McKinsey's global survey, which included Indian organisations, drives the point home from the employer's side. They found that the biggest obstacle to making AI work inside companies is not the workforce. The employees are ready. The obstacle is leadership. Sit with what that means for us. The organisations hiring our graduates are not short of people who can operate the tools. They are short of people who can lead other people through the upheaval the tools create. That gap is our work. That gap is our opportunity.

Three things the machine cannot do

If we are going to redesign how we form young leaders, we had better be precise about where the lasting human value actually sits. The research, and my own years in the room, point to three places.

The first is accountability. A machine can lay out the risks and summarise the rules, but as McKinsey puts it, its role is advisory, not authoritative. It carries no consequence for being wrong. A leader does. When a decision lands on a real person's career, or a team's safety, or an institution's good name, someone human has to carry that weight. There is a line from an old IBM presentation, all the way back in 1979, that the London School of Economics Business Review recently dusted off because it has aged so well.

A graduate who has been taught to take ownership of a difficult call, and to live with what follows, carries something no algorithm can offer. We do not teach that through lectures. We teach it by giving young people real decisions, with real stakes, and refusing to rescue them from the discomfort of choosing.

The second is meaning. Our organisations are drowning in data and starving for sense. AI will happily generate a report. It will not generate conviction. The ability to look at a tangle of complexity and tell a clear, honest, human story about what it means and what we should do — that is leadership, and it is stubbornly, wonderfully human. Which means the things we have long treated as decoration — the ability to write with clarity and speak with force — must move to the very centre of what we teach. I have watched brilliant young analysts lose a room in ninety seconds because no one ever taught them that being right is not the same as being believed.

The third is presence. McKinsey's work on organisational health keeps finding that a leader's decisiveness, accountability, and judgment predict whether a company creates lasting value, and that all of it rests on trust. Trust is not built through a screen. It is built when one human being is genuinely present with another. A young leader who can put the phone down, look someone in the eye, and actually listen holds a skill that grows rarer, and therefore more precious, with every passing year of machine interaction.

At Fortune's Brainstorm AI conference at the end of 2024, a panel of experts landed on the same conclusion from a different direction. Morality and human-level judgment, they agreed, sit among the things this technology simply cannot do. If that is true, and I am convinced it is, then we are not staring at the obsolescence of the educator. We are staring at the most important thing we have ever been asked to do.

The empathy lesson, from a son of Hyderabad

If I had to point a student toward one living example of the leadership this age demands, I would point to a man who grew up in Hyderabad and went on to lead one of the most valuable companies on earth.

Satya Nadella took over a Microsoft that had grown proud, internal, and a little cold. What he brought was not a product. It was a philosophy, and at its heart sat a single word that sounds almost too soft for a technology giant. Empathy. He has spoken openly about where it came from, about raising his son Zain, who lived with severe cerebral palsy, and about watching his wife respond with instinctive care while he, at first, was preoccupied with what it all meant for his own plans.

Read it again, slowly, as a brief for your institution. Teach them to work with the machines, of course. But cultivate the scarce human things — the empathy, the judgment, the plain common sense — because those are what the world will prize. Nadella also did something we, of all people, should admire. He turned a know-it-all culture into a learn-it-all culture. For places whose entire reason to exist is learning, that is not a slogan. It is a calling. We should be sending graduates into the world who are learners for life, not custodians of a fixed lump of knowledge that the next software update will quietly retire.

A story from the floor: Ananya and the jugaad fix

Let me tell you about a young woman I will call Ananya. She is a composite, stitched together from several real graduates I have watched over the past two years, but every beat of what follows has actually happened to someone. I have simply gathered them into one person so you can see the whole shape of it.

Ananya finished a good management programme and joined the analytics team of a mid-sized logistics company in Gurugram. On her second week, her manager handed her a shiny new responsibility. The company had bought an expensive AI forecasting tool, trained largely on Western supply chain data, and she was to use it to predict shipment delays across the company's north Indian routes. Simple, she was told. The machine does the hard part. You just read the output.

The machine did not do the hard part. The forecasts were confidently, expensively wrong. The tool had never seen a Punjab harvest season clog the highways with tractors. It did not know that a single political rally in a district town could freeze movement for a day. It had no concept of the wedding season, when half the trucks in a region vanish to ferry guests and goods. The model was brilliant at patterns it had been fed and blind to the country it was actually operating in.

A lesser response would have been to either trust the machine and watch the company bleed, or to declare the tool useless and ask for it to be scrapped. Ananya did neither. She did something far more Indian, and far more intelligent. She improvised.

She kept the AI tool running for what it was genuinely good at, the broad statistical baseline. Then, on top of it, she built what she cheerfully called her jugaad layer. She called the regional dispatch managers, the men and women who had driven these routes for twenty years, and asked them what the machine could never know. She pulled the local festival calendar. She tracked the mandi auction days that flooded specific roads. She even kept an eye on local news for the rallies and bandhs. None of it was sophisticated. A spreadsheet, a WhatsApp group with the dispatch managers, and a great deal of asking. She fed those human signals back in as adjustments to the machine's forecast.

Within two months her hybrid forecast was beating the expensive tool on its own by a wide margin. The company did not need a better algorithm. It needed a young leader with the resourcefulness to know what the algorithm was missing, and the humility to go and ask the people who knew.

The student who has been taught only to operate the tool will be lost the moment the tool is wrong. The student who has been taught to think, to question, and to improvise will be the one the company cannot do without. We would do well to stop apologising for jugaad and start teaching it on purpose.

So what do we actually do on Monday morning

Philosophy is comfortable. Change is not. Let me put down, as concretely as I can, what I believe the leaders of our universities and business schools can begin doing now.

Make communication the hard currency it has become

Stop treating it as a soft elective. If the ability to persuade and connect is the rising premium skill, then teaching a young person to construct an argument and deliver it well deserves the same seriousness we give to a finance core. Every student should leave able to walk into a room and move it. I promise you the market will pay for this more reliably than for one more spreadsheet skill.

Build judgment the only way it has ever been built — through experience

Cases, simulations, live projects, decisions that carry real consequences. Wharton pairs its technical content with organisational behaviour and ethics for exactly this reason. Let students make hard calls, defend them out loud, and feel the weight when they get it wrong. That sting teaches what no lecture can.

Treat ethics as a habit of mind, not a box to tick

In 2024 an airline was held liable by a court for wrong information its own AI chatbot had given a customer. No algorithm was blamed. A company was. Our graduates will spend their careers accountable for what their machines produce. Ethics cannot live in one quarantined course. It has to run through everything, the way a watermark runs through paper.

Make room for the inner work

McKinsey explicitly argues that leaders need time to reflect, and yet reflection is the first thing we squeeze out of a crowded timetable. Mentorship, quiet, the deliberate building of self-awareness — these are not indulgences. A young person who does not understand their own blind spots will lead badly no matter how fluent they are with the latest tool.

Let our faculty be mentors in the art of being human

This generation arrives fluent in the machine but often short on patience, on depth, on the ability to sit with a hard problem instead of reaching for the search bar. That is precisely where an experienced teacher becomes irreplaceable — not as a deliverer of facts a machine can recite faster, but as a living model of the human capacities that hold leadership together. The teacher's worth is shifting from what they know to who they help a young person become. I find that shift not threatening but thrilling. It is, after all, why most of us started teaching in the first place.

None of this is an argument against AI in our classrooms. Use it. Let it take the drudgery, the first drafts, the routine, so that our precious hours with students can go to the things that cannot be automated — the argument, the debate, the mentorship, the slow and human work of forming character.

What I tell my students

I have taught in many rooms, from the Army War College to business schools scattered across this country, and the questions students ask have shifted under my feet. They no longer ask whether AI will touch their careers. They have made their peace with that. What they ask now, sometimes openly and sometimes only with their eyes, is quieter and more frightened. What will still be mine?

My answer does not change. What stays yours is your judgment. Your character. Your capacity to sit across from another human being and actually see them. Your ability to tell a story true enough and clear enough to move people to act. The machine will draft your report, but it will never earn the loyalty of your team. It will lay out your options, but it will never carry the weight of your choice. It will hand you answers all day long. It will never hand you wisdom.

The institutions that understand this — that refuse to fight the machine on the machine's own ground and instead pour themselves into the deeply human work of building leaders — will send out into India and the world the people we most need. The ones that do not will keep preparing students for a race they cannot win, against an opponent that never sleeps and never tires.