– Abhimanyu Saxena, Co-Founder, Scaler and Scaler School of Business

For years, management education has been declared obsolete at regular intervals, often during moments of economic uncertainty or technological change. Artificial intelligence has reignited that debate, with a familiar question resurfacing: Will AI make management education irrelevant?

It is the wrong question.

AI is not eliminating the need for business leadership. What it is steadily dismantling are the execution-heavy roles that once served as the apprenticeship ladder for management careers. Management education is not losing relevance; the pathways it traditionally prepared people for are being fundamentally reshaped.

For decades, management careers followed a predictable arc. Graduates of management programmes would begin in analytical or coordination-heavy roles, learning the mechanics of business through repetition and gradual responsibility. These early roles, often unglamorous, were where judgment was built, context was absorbed, and leadership instincts were formed.

That ladder is now thinning.

Tasks that once defined early management roles — such as data analysis, forecasting, reporting, performance tracking, and process optimisation — are increasingly automated. What previously required teams of junior analysts working for weeks can now be generated in hours. Bloomberg recently found that AI could replace more than half the tasks performed by market research analysts (53%) and sales representatives (67%), compared to just 9% and 21%, respectively, for managerial roles. The implication is clear: execution-heavy roles are far more exposed to automation than decision-making ones.

Roles such as junior analysts, marketing performance trackers, operations coordinators, and finance forecasters are not disappearing overnight, but their scope is narrowing and their learning value is diminishing. What once served as a training ground for leadership is becoming a bottleneck.

Much of the anxiety surrounding management education today stems from this shift. It is not that management learning has lost relevance; rather, the traditional “learning by execution” phase is no longer guaranteed.

This shift matters deeply in the Indian context. India adds millions of graduates to the workforce each year, many of whom view management education as a pathway to leadership and upward mobility. Yet a recent TeamLease report suggests that, despite a growing national focus on job readiness, only 16.67% of institutions achieve placement rates of 76–100% within six months of graduation. As early-career roles compress, the gap between education and real responsibility widens unless institutions actively adapt.

At the same time, employer expectations are clearly evolving. According to Gartner, 80% of leadership roles posted today prioritise strategic thinking and innovation over operational efficiency. Organisations are signalling that they value judgment, synthesis, and long-term decision-making far more than functional execution.

As routine execution becomes automated, responsibility is moving upward. Organisations need fewer people to run processes and more people who can decide what should be done, why it matters, and what trade-offs it involves. The distance between analysis and accountability is shrinking.

This is giving rise to a new class of leadership roles. Managers are increasingly expected to translate insights into strategy, prioritise initiatives based on long-term impact, balance customer needs with technological and financial constraints, design systems rather than manage processes, and align teams across functions with competing incentives.

These roles demand judgment much earlier in a career. They do not wait for years of functional seasoning. Many professionals are now expected to think and act like leaders without having spent a decade climbing the rungs of the execution ladder.

This is where management education still matters — but in a very different way than before.

The future value of management education will not lie in teaching people how to build models, manage dashboards, or optimise workflows. Intelligent systems already do those things faster and at scale. The differentiator will be judgment: the ability to make high-stakes decisions under uncertainty, with incomplete information, and with real consequences.

This is not about “learning AI tools.” It is about learning how to work alongside intelligent systems without surrendering accountability. Effective leaders will treat automated outputs as inputs, not answers. As algorithmic decisions increasingly shape hiring, lending, pricing, and access, leadership will be defined not just by efficiency but by foresight and restraint.

Encouragingly, some institutions are already responding. Forward-thinking business schools globally are re-evaluating their core management offerings, introducing mandatory modules on AI ethics and governance, scenario planning, and complex decision-making under uncertainty. The focus is shifting away from rote functional learning toward experiential, decision-led education that mirrors real-world ambiguity.

If the nature of management is changing, management education must change with it. Institutions can no longer rely on curricula built primarily around functional execution. Teaching students what to analyse matters less than teaching them how to decide when analyses conflict, data is noisy, or outcomes are ambiguous.

AI is not eliminating management education. It is eliminating the comfort of apprenticeship roles that once served as a slow on-ramp to leadership.

The future graduate of management education will step into organisations as a decision architect, responsible for integrating machine intelligence with human judgment, ethical reasoning, and strategic accountability. This is a heavier responsibility, but also a more meaningful one.

Management education is not being replaced. It is being redefined. And in that redefinition lies its most important opportunity yet.

Also Read: How Leadership & Management Programmes Must Evolve for Gen Z & Alpha