Recalibrating Pedagogy in Contemporary Times - Unteachable Moment: Why professors must change before students leave

Paulo Freire’s seminal work ‘Pedagogy of the Oppressed’ based on critical pedagogy deserves to be deliberated in the epoch of artificial intelligence (AI) and AI-based teaching-learning process. Freire’s argument can be validated in the realm of dialogical education in the era of algorithms, contemporary and practice-oriented, and humanizing education in an automated world.

In a sunlit classroom in Bangalore, moments before the lecture begins, a second-year MBA student, Sunita (name changed) opens her laptop. She’s not checking her email. She’s not browsing LinkedIn. She’s automating a newsletter using Make.com, one that curates trending AI tools for mid-sized marketing agencies. Her monetization model? A freemium GPT-powered Chatbot embedded in her Substack, recommending tools to early-stage startup founders. It’s built using Chipp.ai and trained on custom prompts she developed using OpenAI’s API docs.

Sunita is not from IIT. She doesn’t code full-time. She has marketing major. And she’s not alone. Across India—from Hyderabad to Ahmadabad, from Gurgaon to Guwahati—MBA students aren’t waiting to be shown the future of digital marketing. They’re already shaping it. If professors aren’t careful, they won’t just fall behind—they’ll be rendered irrelevant, speaking a professional dialect their students no longer understand.

What’s unfolding in Indian educational programs isn’t a quiet shift. It’s a reordering of pedagogical power. The traditional classroom hierarchy where professors teach and students absorb—has been upended by a generation of learners who build, automate, and experiment before the syllabus catches up.

That student is automating her newsletter? She’s not exceptional, she’s typical. Today’s students from business and commerce streams are using Zapier to connect Slack and Asana boards, feeding user data from Instagram via Phantombuster, spinning up campaign visuals in Uizard, and generating emotional ad copy with Jasper. They’re building GPT-powered personas in Google Sheets and using AI tools not to replace effort but to amplify it. These aren’t just digital marketing students, they’re AI-native growth hackers.And no, they’re not being arrogant. They’re being urgent. Because in a world where they’ll soon compete for roles at Razorpay, Meesho, or Zepto, knowing theory without automation is like bringing a whiteboard to a server farm.

This shift has exposed a widening gap—not of knowledge, but of translation. Many faculty members, especially outside India’s top-tier institutions, are still wrestling with LMS portals while their students are testing Talon. One for micro-ads or using Marble Flows to create on boarding flows that outperform agency work.

It’s not that professors don’t have insight. They do decades of it. But too often, that insight is buried in analog models. They speak in terms of Porter’s 5 Forces and the McKinsey 7S, unaware that their students are experimenting with Claude to analyze influencer performance or using Runway ML to auto-generate reels from campaign scripts. Today’s students don’t see digital marketing as a subject. They see it as a system, a constantly evolving ecosystem of tools, data, triggers, and automation logic.

In contemporary times, students aren’t asking professors to become tool encyclopedias. They are far from it.That distinction is everything. Because the real demand isn’t for more martech content—it’s for logic. For structured thinking. For understanding why a tool exists, how it fits into a broader strategy, and when to question its use. Students want a map of the terrain, not just a tour of the landmarks.They’re not just interested in building chatbots, they’re building revenue engines that recommend dynamic pricing based on user behavior. They’re not content with discussing brand personas—they’re testing psychographic clusters built from Reddit comment sentiment. This is no longer the age of the digital marketer. It’s the age of the AI-native strategist.

What makes this moment even more complex and urgent is the ethical terrain students are beginning to explore. With India’s Digital Personal Data Protection Act (DPDPA) now in force, today’s students aren’t just asking what AI can do. They’re asking what it should do. Is it ethical to scrape WhatsApp group behavior for retargeting? Should we use sentiment analysis from voice notes via AssemblyAI to optimize ads? Can we build psychographic models without violating consent?Students are ready to confront these questions. But only if someone guides the conversation. If professors don’t, Reddit threads and YouTube tutorials will and that’s a risk academia shouldn’t take.

Some institutions and faculty are responding. IIMs are experimenting with sandbox-based modules. A few private colleges are partnering with SaaS startups to offer micro-credentials. And some visionary professors are already turning classrooms into campaign labs, running SEO simulations with GrowthBar, or inviting virtual guest speakers via Synthesi aavatars.But these are exceptions. But it is not the rule.

Most professors still refer to ChatGPT as a “content generator,” unaware that students are using it—paired with Code Interpreter to simulate budget sheets, generate campaign variants, or build Slack bots via Replit that trigger alerts when ROAS drops below a threshold.The tools have changed. The expectations have changed. The pedagogy, too, must now change.

The question we must ask isn’t how to add AI to the syllabus. It’s how to make AI the lens through which we interpret the syllabus.A marketing class in 2025 isn’t just a place to talk about campaigns. It’s a space to build them, test them, and break them, using tools like Hotjar, Lemlist, Cohere, VWO, and LangChain. It’s a lab, not a lecture hall.

Students don’t want to memorize brand models. They want to reverse-engineer the logic behind Amazon’s recommendation engine. They don’t just want to analyze case studies, they want to simulate them, test different hypotheses, and interpret outcomes through the logic of systems thinking.The future of teaching isn’t about replacing theory with tools. It’s about weaving them together, teaching not just what works, but why, how, and at what cost.

Let’s be clear. This isn’t a crisis of expertise. It’s a crisis of communication.Professors still hold irreplaceable value deep insight, strategic perspective, and ethical grounding. But if they don’t learn to express that value through today’s tools and systems, their wisdom won’t land. Students won’t disengage out of disrespect, but out of necessity. They need answers. And if those answers don’t come from the classroom, they’ll find them elsewhere. The challenge isn’t that students are moving too fast. It’s that institutions are moving too slow.

And yet, beneath all the tools and dashboards, amid the martech overload and automation euphoria—there’s something deeply human happening.Students aren’t just asking for shortcuts. They’re asking for mentors who can reason with them. Think with them. Challenge them. They want professors who can explore complexity with curiosity and rigor. Who can ask not only what works, but what matters. If we meet them there, the classroom will not only survive this revolution rather it could lead it. Because the future of marketing isn’t being built in boardrooms or textbooks. It’s being built at the desks of students who’ve stopped waiting.

(Chakraborty is an Associate Professor at TA Pai Management Institute (TAPMI), Bengaluru Campus, Manipal Academy of Higher Education, Manipal. Biswal is an Associate Professor at Department of Journalism and Mass Communication, Rama Devi Women’s University, Bhubaneswar)