Last Updated on September 21, 2026
MBAUniverse.com News Desk
How can management education keep its relevance and integrity in the age when AI can write essays, analyse complex data, and crack the management case in minutes? That question ran through the panels at 16th Indian Management Conclave (IMC) 2026, held at the IIM Lucknow Noida Campus on 18 and 19 September 2026. High-powered panels of Directors, Deans and Vice-Chancellors from India’s leading business schools reached a striking consensus: the unregulated use of Artificial Intelligence in MBA classrooms poses a grave threat to genuine learning, and the time to act thoughtfully is now.
Setting the stage with a research-intensive opening address, Dr Amit Agnihotri, Founder & Chair of the Indian Management Conclave, laid out seven concerns for the sector. The panels that followed brought together Dr Rishikesha T. Krishnan, Vice-Chancellor, Ashoka University; Dr Varun Nagaraj, Dean, SPJIMR Mumbai; Dr Arvind Sahay, Director, MDI Gurgaon; Dr Suresh Ramanathan, CEO, IMI Delhi, Kolkata & Bhubaneswar; Dr Madhu Veeraraghavan, Pro Vice-Chancellor, Manipal University (MAHE); Prof Vishal Karungulam, Academic Director of ISB’s Centre for Learning & Teaching Excellence and Lab; and Dr Atish Chattopadhyay, Director, IMT Ghaziabad. The sessions were moderated by Dr Radhika Shrivastava, President, FIIB New Delhi, and Mr Dviwesh Mehta, Director, Asia Pacific, Harvard Business Impact.
None of the speakers disputed AI’s promise. Used well, AI can speed the creation of teaching material, offer students a 24x7 adaptive tutor, enrich simulations and experiential learning, and accelerate research. Yet the mood in the room was one of urgency rather than celebration. The worry of academic leaders was specific and practical: when students reach for AI to produce answers directly rather than to build the ability, the very cognitive effort that produces learning is bypassed. What follows captures the challenge as the panels defined it, the solutions they proposed, and their pointed message to the AI technology industry.
Before discussing the concerns, the promise of AI for management education is worth stating. Academic leaders agreed that AI can generate innovative teaching materials and instant feedback, act as a patient round-the-clock tutor that adapts to each learner, power simulations, gamified exercises and immersive, VR-enabled environments, and compress weeks of data analysis into hours. The same capabilities that can deepen learning, however, can just as easily replace it.
THE CHALLENGE: WHY UNREGULATED AI USE IN MBA CLASS IS A THREAT
AI is redrawing the workplace, and the MBA must keep pace
The panel’s starting point was the world of work into which MBA graduates step. Dr Rishikesha T. Krishnan observed that workplace requirements are changing rapidly as AI-driven workflows reshape how tasks are done, and that management education must keep pace or risk irrelevance. Dr Madhu Veeraraghavan sharpened the point: “AI is transforming business, the future of work will look very different, and as new jobs are created and old ones disappear, the competencies and skills that employers value will shift accordingly.”
The implication for business schools is uncomfortable. MBA program and curriculum designed for a pre-AI workplace, however rigorous, may be preparing graduates for roles that are being redefined even as they study. The challenge is not simply to add AI to the syllabus, but to rethink what a capable manager needs to know and be able to do when routine analysis is increasingly automated. The moderators, Dr Radhika Shrivastava and Mr Dviwesh Mehta, pressed the panel to move beyond diagnosis to prescription, steering the discussion from what AI is doing to management education towards what management education must now do about it.
Unregulated AI is eroding the “good friction” that produces learning
If the first challenge is relevance, the second is deeper and more troubling: the risk that AI, used carelessly, quietly hollows out learning itself. Dr Varun Nagaraj framed this as the loss of “good friction.” Real learning, he argued, happens when students struggle with concepts that are new to them, and it is precisely that productive struggle that AI can remove. When MBA students turn to AI tools for readymade answers, the friction disappears, and so does much of the learning. Dr Arvind Sahay made the same case from cognitive science: “the human brain learns from the challenge that new material and hard problems pose, a process central to genuine assimilation, so if students rely on AI for most of their analysis, their learning is bound to suffer.”
Dr Suresh Ramanathan warned that excessive and unthoughtful use of AI in the MBA classroom poses a real and immediate challenge to student learning, while Prof Vishal Karungulam noted that AI has been adopted rapidly by both students and faculty at business schools, and that although the benefits are real, unregulated student use may undermine the very learning outcomes the programme exists to deliver.
The panel’s concern, in short, was not that students use AI, but that they use it to skip the thinking. Management education must therefore be thoughtful about how it evolves in the age of AI, so that the tool supports learning rather than substituting for it. Emerging evidence gives these worries teeth, as Dr Agnihotri’s address would go on to demonstrate with research insights from major studies in the world.
A measured counterpoint: build strong, aspiration-aligned foundations
Not every voice on the panel viewed the moment with alarm. Dr Atish Chattopadhyay, Director of IMT Ghaziabad, offered a deliberately measured counterpoint, saying he was not overly concerned about the advent of AI and its impact on MBA education. His argument was that if business schools build strong foundations and competencies aligned to the aspirational roles their graduates seek, they will remain valuable whatever the tools of the day.
Seven concerns for management education: Dr Amit Agnihotri’s opening address
In his opening address, Dr Amit Agnihotri framed the debate with evidence and set out seven concerns that, taken together, define the agenda for management education in the age of AI.
THE WAY FORWARD: JUDGEMENT-CENTRED AI ADOPTION
The moderators, Dr Radhika Shrivastava and Mr Dviwesh Mehta, asked the panel to recommend way forward for the management education.
Teach every discipline through the lens of AI
For Dr Rishikesha T. Krishnan, the way forward begins with the core rather than with a bolt-on technology module. Traditional functional knowledge and disciplines, from finance and marketing to operations and strategy, should be taught with a clear view of how AI is influencing and changing each of them. In this approach, AI is not a separate subject sitting alongside the syllabus, but a lens through which every discipline is now taught, so that graduates understand both the enduring fundamentals and the ways those fundamentals are being transformed in practice. Done well, this closes the gap between what schools teach and what an AI-shaped workplace actually requires.
Thoughtful AI use: analyse, judge, and own the output
Where the panel converged most strongly was on the difference between using AI to get answers and using it to build judgement. Dr Varun Nagaraj, Dr Arvind Sahay and Dr Suresh Ramanathan each argued for the thoughtful use of AI: programmes should require students to analyse the strengths and weaknesses of AI outputs, form their own judgement, and take ownership of it. Rather than accepting a AI tool’s recommendation at face value, students would be asked to interrogate it, identify where it is wrong or incomplete, and defend a considered position of their own.
In practice, this reframes many familiar assignments. A student might be asked not to write a market-entry recommendation, but to critique an AI-generated one: to find the flawed assumption, the missing data and the risk the model overlooked, and then to produce a better-reasoned answer that they sign in their own name. Assessed this way, AI output becomes the raw material for further analysis and judgement rather than a substitute for it.
Bring back the viva, and centre critical thinking, judgement and people skills
Several speakers were willing to reach for older tools to solve a new problem. Both Dr Nagaraj and Dr Sahay called for a return to the viva voce, conducted without AI tools, as a direct and honest test of what a student actually understands. Dr Sahay shared that MDI Gurgaon is planning a range of interventions along these lines, with programmes designed to build critical thinking, judgement and the people skills that AI cannot supply. The logic is straightforward: if written submissions can be produced by a machine, assessment must move to settings where a student has to think, explain and defend in real time. In an era of readily generated text, the oral examination and the live defence become powerful again, precisely because they cannot be outsourced.
Dr Suresh Ramanathan of IMI framed the same shift as a decisive move towards continuous, application-based assessment, though he would not discard examinations altogether. A well-designed examination, he noted, can still show whether a student has mastered essential concepts; the danger arises when a memory-heavy end-term paper becomes the main evidence of learning. In its place, students should write decision memos, build models and dashboards, make presentations, work through simulations and live projects, and defend their reasoning orally, formats that reveal how a student framed the problem, chose evidence, exercised judgement and communicated a decision.
Every assignment, he added, must state whether AI is prohibited, allowed with disclosure, or an essential part of the task, and where it is used, students may have to show their process, verify sources and calculations, and defend their choices in a viva. As Dr Ramanathan put it: “We cannot pretend that AI can be kept outside education. We also cannot confuse a fluent machine-generated answer with evidence that a student has learnt.”
Reimagine the MBA to be more human
Dr Madhu Veeraraghavan located the way forward in the changing world of work. As AI transforms business and the competencies required for the future shift, he argued that the time has come to make the MBA more “human,” with a judgement-focused programme designed explicitly for the AI era.
Institutions are already moving in this direction, and IMI offers a detailed example. Dr Suresh Ramanathan described a curriculum revamp built on the conviction that AI cannot be treated as a single elective. “AI cannot be placed in one elective, examined at the end of the term, and then declared covered,” he said. “It is already changing work in marketing, finance, operations, human resources, strategy, and entrepreneurship. Students must encounter it in each of these settings.”
Read together, these views point to a single design principle. The MBA of the AI era should be more human, not less, using AI to handle routine cognition while investing scarce classroom time in the distinctly human capabilities that decide who leads.
A CALL FOR AI COMPANIES TO COLLABORATE
If the panel had one message for the technology industry, it was this: today’s AI models do not, on their own, facilitate real learning in management education. Dr Nagaraj and Dr Sahay were explicit that AI providers must collaborate with business schools and universities to adapt their models so that they facilitate, rather than short-circuit, student learning.
Building such higher education context centric models and tools, the speakers argued, cannot be left to educators alone. It requires a genuine partnership between AI companies and the academic community, with pedagogy, and not only productivity, as the design goal. This is a significant ask of an industry whose products are built for convenience, but the panel’s case was that the stakes for a generation of managers justify it.
Dr Amit Agnihotri proposed that the Indian Management Conclave, as a scholarly forum, is ready to support this transition and to convene business schools and AI providers around a shared, learning-first agenda, translating the debate on stage into concrete collaboration.
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