ASK ANY DEAN what big trends are impacting business schools, and AI will top their list. I’ll do the same, but with a slightly different interpretation of AI as both a friend and a foe.

As AI becomes a reality, every business school must determine how it will affect the industries in which our graduates will work. At SPJIMR, the approach is two-fold: first, to understand how AI is transforming business practices, and second, to understand how AI is changing the learning and teaching experience.

From the science and art of marketing at an FMCG company to portfolio analysis at an investment management firm and route planning for a quick commerce company, AI is transforming how business is practised.

Hence, we’ve started introducing AI use cases and examples in our courses. When industry says students need to “know” AI, they don’t mean using prompt engineering to generate reports; they mean understanding how it applies to real-world contexts like customer experience, decision systems, and supply chains. Students also need to build the models that will help them solve real-world problems. I want all our students to be able to design, code, and prototype their own ideas, regardless of their specialisation.

The deeper challenge

The second part of AI’s impact is more fundamental — it changes what professors do and how students learn. At SPJIMR, faculty are encouraged to experiment and integrate AI across every phase of learning: pre-class preparation, in-class participation, post-class reflection, and even evaluation.

From a governance point of view, we’re not taking a ‘one-size-fits-all’ approach; we encourage experimentation because we don’t yet know what works best. This also keeps our faculty intellectually alert, in what I call a ‘virus-antivirus’ dynamic with how learners use AI.

The big danger of AI is that it potentially short-circuits the learning process entirely. It compromises who we are as human beings and undermines the basic skills we need. Take a simple but essential set of human abilities: socialisation, communication, and connecting with people. We already know that social media has reduced some of these abilities. AI reduces it even more. Curiosity is disappearing among people. The ability to concentrate for long periods of time is being compromised because everything is instantaneous. The ability to solve hard problems is also declining.

The answer is not to say, “don’t use AI in the classroom.” We have to rethink our curriculum to ensure these human attributes don’t get lost.

Framework for understanding

In their working paper titled How Generative AI Reshapes Management Education: From Algorithmic Threats to Structured Social Learning, Ivey Business School’s Julian Birkinshaw and Maziar Raz theorise three mechanisms through which GenAI threatens management learning. It resonates with what we observe today. First is ‘algorithmic short-circuiting of conceptual knowledge’, where learners bypass the cognitive struggle required for deep understanding. Second is ‘algorithmic displacement of skills’, where technical competencies and social capabilities atrophy through substitution. Third comes ‘algorithmic decontextualisation of practical wisdom’, which removes judgement from its social, historical, and imaginative contexts.

This framework builds on Aristotle’s distinction between three types of knowledge — episteme (concepts), techne (skills), and phronesis (practical judgement). GenAI’s growing influence, if unchecked, threatens each of these: it weakens conceptual learning, displaces skill-building, and undermines human judgement. I worry the most about judgement — probably the most important competency a manager or leader should have.

AI ‘speaks’ authoritatively, often without fully substantiated evidence. The more individuals outsource thinking and decision-making to AI, the less they engage in trial and error — the process through which wisdom and moral judgement evolve.

In other words, the danger is not that AI will replace humans in learning, but that it may quietly erode what makes learning human — curiosity, concentration, empathy — the ability to make meaning from complexity and judge what is right and wrong in specific contexts.

Preserving the human core

At SPJIMR, we are rethinking our curriculum to ensure these human attributes don’t get lost. We have made ‘Systems Thinking’ a compulsory course to help students think deeply and connect ideas. We are piloting a course on ‘Critical Thinking with AI’ because AI can enhance and destroy critical thinking — and plan to make it a core offering next year. We are piloting a module on ‘Computational Thinking’, to allow our learners engage with and use technology aptly. Our ‘History of Capitalism’ course has been expanded to strengthen contextual understanding, and we’re doubling down on hands-on experiential learning — social projects, rural immersions, and start-up collaborations — to nurture empathy and real-world connections.

AI also allows faculty to benchmark and redesign courses, create short real-time cases, and tailor learning materials. But faculty need to think more deeply about how to use AI in the learning process to develop human skills. We can have students alternate between solving problems with and without AI to compare outcomes. I am optimistic about AI’s potential to provide oral discussions and feedback at scale. Done right, AI could create between faculty and learners the kind of relationship Alexander had with Aristotle. 

The humanism imperative

AI is eroding human qualities, and we must take conscious steps to address that. It helps scale learning, but cannot replace the social nature of business education and business practice. The future of management education lies in embracing AI wisely: ensuring that as machines get smarter, humans become more thoughtful, compassionate, and self-aware in their use of technology to create positive outcomes for themselves, organisations, and society at large. At SPJIMR, that’s what ‘wise innovation’ means.

(The author is Dean, SP Jain Institute of Management & Research. Views are personal.)