By Oliver Lyngdoh
Welcome to the world of Tomorrow, Today!
In many classrooms of public and private institutions, there is now a huge difference in the appearances and infrastructure as compared to the traditional classrooms where we studied. Smart Classrooms with intelligent touch-screens are the norm now even in the outskirts of any ‘smart’ city. Students of tomorrow or should I say of today, do not flip pages or scribble down notes, they now converse with personalised AI tutors, submit essays and reports prompted via generative AIs and solve math problems on smart boards which are instantly corrected and explained by learning AI Bots.
Many institutions now proudly proclaim themselves to be “Smart Campuses”.
However, as AI-driven methodologies seep into the very heart of education, a significant question looms over the future of learning: What are we trading off in the name of convenience, speed, and precision?
Artificial Intelligence (AI) in education is no longer a concept of sci-fi movies; educational institutions all over are increasingly integrating AI Tools (read ChatGPT, Gemini, Claude etc) and AI enabled and enhanced learning platforms (read Coursera, Smart Sparrow, Course Magic etc) into their learning activities. AI is being used in a wide range of academic related activities – from personalized learning paths, courses and grading automation to real-time feedback and virtual tutoring. Digital Avatars in the Metaverse are even being introduced as a form of tutoring for distant and online courses.
AI, its benefits and contributions towards the education sector are undeniably significant since using AI, educators can tailor content to suit different students, help break down complex concepts, and offer 24/7 accessibility which in turn can help address issues like student-teacher ratios and inconsistent teaching quality. It’s the answer to many inefficiencies in the current education sector.
However, this article isn’t focused on what AI might contribute — it’s about how overreliance on it could undermine the very essence of education.
The process of learning has always been deeply intertwined with struggle- to grasp complex ideas, to experience failure and success, to iteratively refine conceptual understanding in order to develop analytical and problem-solving abilities. AI, however, offers immediate solutions through prompts and queries, thereby diminishing the space for productive thinking.
The general narrative from old school educators is that students no longer want to explore problems themselves. Students amongst the entire current generation of people are conditioned to expect answers without the struggle to thoroughly grasp or learn the subject matter. We are excellent at refining AI queries and generative prompts but not necessarily at refining thought processes.
This reflects a shift from thinking to prompting, from building mental models to asking AI to generate them. The result is a paradox: students can produce polished assignments and projects but often falter when asked to explain their rationale without digital assistance.
There has been a reported drop in the ability of students and the current generation as a whole to solve open-ended reasoning problems without technological aid, compared to high schoolers in the early millennia. This echoes’ concerns raised by educators, cognitive and behavioural scientists that the over-dependence on AI Tools may dull critical thinking and reasoning abilities in the formative years.
It may be noted that logical reasoning isn’t just about arriving at the correct answer—it’s about the thought process and the rationale behind arriving at the solution which demands cognitive patience, the ability to hold multiple ideas in mind, to weigh, debate, and synthesize. These are habitual traits and not just skills. And habits are hard to form when external tools keep intervening before internal thinking even begins.
An aspect that is often overlooked in this shift is the impact on the educators themselves. As AI tools are increasingly being adopted and embedded into curriculum, teaching methods, grading, documentation, administration and even communication, educators now find themselves delegating core responsibilities to machines. Planning Lessons, for example, which was once a well thought out methodology, personalization and creative thought process, is now frequently being prompted into AI powered systems that generate content based on existing data and templates.
The process and the act of teaching is then substituted into the process of managing AI tools. Educators become facilitators of content rather than mentors cultivating young minds. Digital immersive avatars and online tutoring would lead to educators spending more time curating AI-generated content or reviewing algorithmically graded assignments than interacting with students directly.
Overreliance is dangerous.
When educators stop ‘thinking’ as teachers and start operating like AI technicians, the essence of education—human connection, moral reflection, spontaneous insight—will be diluted. The classroom – wherever the classroom will be – will become a transactional space instead of a transformational space.
The worse might happen when institutions will use AI as a justification to reduce investment in training, mentorship programs and experiential learning as “AI can teach better”. This worrying mindset will under evaluate the teaching profession itself.
Pushing AI to generate lesson plans, lecture content, grading and evaluating assessments, educators might be pushed into the role of content managers and moderators (Perhaps, some might argue that this may be a new career path). However, the empathetic human element of teaching, off-script storytelling, spontaneous debates, and one-on-one nudges of encouragement—will be minimized. These are needed for mentorship, inspiration and challenge.
Young minds may inadvertently be taught that reflection and creativity are dispensable if educators rely solely on outsourced thought processes via AI tools. This passive consumption of AI-curated knowledge is the antithesis of an engaged learning environment.
The biggest irony is that, while industries are embracing AI, they are continuously seeking ‘human’ workers who can not only ‘prompt’ AI but can complement it. A World Economic Forum report highlighted that the top future job skills include “complex problem solving”, “originality”, “emotional intelligence”, and “systems analysis”. Yet, if students grow up bypassing these processes thanks to AI tools, they might risk becoming “AI middle managers”—people skilled at using tools but not thinking beyond them.
This raises a chilling concern: Will the future workforce be smart users of AI or intellectually dependent on it?
While acknowledging that AI will shape the coming generation, a failure to cultivate critical thinking and imaginative capacity could leave them as mere cogs, lacking the originality and leadership spark needed to navigate a hyper-automated world.
The wide spread sudden adoption and trend of AI has also introduced a hidden bias in access. While elite institutions can afford sophisticated AI infrastructure, rural and underfunded institutions cannot. This AI divide reinforces educational inequalities. Students with high intrinsic motivation and a strong foundational base are more likely to use AI as a learning aid. Others may lean on it as a crutch. This will further deepen the education divide and skill acquisition. AI, rather than levelling the playing field, risks becoming a new axis of division.
To be clear, this isn’t an argument for rejecting AI in education.
The challenge is not AI itself, but uncritical and unbalanced dependence on it—especially in early education stages when cognitive and emotional habits are still forming.
AI and AI enabled tools should be used to augment teaching and the education process and should not replace it. Critiquing AI generated essays and assignments will help build evaluative thinking. Limiting the use of AI in formative assessments will encourage reliance on critical thinking and reasoning. Designing classroom activities that prioritize discussion, ambiguity, and open-ended exploration will prevent over-reliance on AI powered solutions.
Educators must be trained not just in using AI, but in understanding its pedagogical boundaries. The curriculum should evolve to teach with AI, not through it. Over reliance on a machine should not be encouraged.
As we embark on the path of an AI-enhanced future, education is set to evolve. We stand to gain more from AI and AI enabled tools generally than what we may presume to lose but neither concern is misplaced.
The crucial question is whether we aim to cultivate independent learners or a generation that merely outsources its curiosity to the algorithms of AI and its datasets?
The future of education demands a thoughtful, human-centred, and critical intelligence, not just artificial intelligence. A holistic intelligence should be the definition of knowledge, even in an AI-driven world.