by Dr. Brotati Chakraborty / Dr. Prasanta Gayen
What happens when the machine that knows everything begins to enter the classroom, but the teacher has less time to know the child? This is the paradox at the heart of the artificial intelligence revolution in education. AI can explain a difficult concept in seconds, generate an essay, translate a lesson, personalise learning materials and provide instant feedback. It can analyse patterns in student performance that might take a teacher hours to identify. Yet education has never been simply about delivering information. A machine can produce an answer, but can it recognise the silence of a student who has lost confidence? It can identify declining academic performance, but can it understand whether the cause is anxiety, family pressure, poverty or loneliness?
The central question, therefore, is no longer whether AI will enter the classroom – it already has. The real question is whether, in our rush to make education smarter, faster and more efficient, we risk making it less human. Used wisely, AI could give teachers something education systems have long struggled to provide: more time to listen, mentor, encourage and connect. Used carelessly, however, it could turn the classroom into a data-driven space where efficiency replaces empathy and personalisation is mistaken for genuine human attention.
The most constructive way to understand AI in education is not as a replacement for teachers but as a tool for augmenting human capability. Teachers devote enormous time to routine tasks such as preparing instructional materials, creating worksheets, generating assessments, organising information and compiling reports. AI can potentially reduce some of this workload, allowing educators to spend more time on discussion, mentoring, collaborative learning and individual support. It can also help students receive explanations according to their learning needs and provide additional opportunities for practice. But technological personalisation should not be confused with genuine individual attention. Students are not simply collections of marks, behavioural patterns and learning preferences.
A student who repeatedly submits assignments late may appear academically disengaged, while the actual reason may be family responsibilities, financial difficulties, emotional pressure or a lack of confidence. An algorithm can identify a pattern; a teacher must understand its context. AI may tell us what a student has done, but a teacher often has to discover why. This distinction will become increasingly important as educational institutions collect more student data and depend more heavily on automated systems. The purpose of technology should therefore be to strengthen the teacher-student relationship, not to make that relationship unnecessary.
Generative AI is also forcing education to confront an uncomfortable question: if a machine can produce the answer, what exactly should the student be learning? Consider a familiar Indian classroom. A Class VIII teacher in a government school asks students to write a short paragraph in English on “My Village.” A student who struggles with English uses an AI-enabled tool to produce a polished paragraph. If the teacher simply marks the submission, the exercise may measure the student’s access to technology rather than the student’s language ability. But imagine the teacher using that same AI-generated paragraph differently: asking the student to read it aloud, identify unfamiliar words, explain the ideas in Bengali or Hindi, rewrite two sentences in their own words and describe their actual village to the class. Suddenly, AI is no longer doing the learning for the student; it is becoming a starting point for learning. This small example captures the larger challenge.
Students must learn not only how to use AI, but how to question, verify, adapt and improve what AI produces. Instead of simply asking learners to write essays, teachers can ask them to examine AI-generated responses, identify factual weaknesses, verify evidence and develop stronger arguments. For India, this approach is particularly important because classrooms differ enormously in language, geography, socioeconomic conditions, digital access and institutional resources. AI can support multilingual education, learners with disabilities and students requiring additional academic assistance, but technological progress without digital inclusion could deepen existing inequalities. The AI classroom must therefore be accompanied by teacher training, equitable access, data protection and ethical safeguards.
The arrival of AI does not make the teacher less important; paradoxically, it makes the teacher more important. When information becomes abundant, the educator’s value lies less in possessing information and more in helping students interpret, question and apply it. Teachers will increasingly need to become facilitators, mentors, designers of learning experiences and ethical guides. They will also need to know when not to use AI. Not every educational problem requires a technological solution. Sometimes a student needs a conversation rather than a chatbot, encouragement rather than automated feedback, or a classroom debate rather than another digital activity.
The future classroom will undoubtedly contain more AI, but the real measure of progress should not be the number of algorithms installed in schools and universities. It should be whether students emerge more curious, more critical, more compassionate and more capable of thinking independently. AI can make education more personalised, efficient and accessible, but it cannot decide what kind of human beings education should help us become. That responsibility remains ours. The future should therefore not be framed as AI versus the teacher, but as AI in the service of the teacher and technology in the service of the learner. If education is ultimately about preparing human beings to understand the world and one another, then the greatest success of artificial intelligence may not be teaching machines to behave more like humans. It may be giving human teachers more time to do what machines cannot: see the person behind the performance, hear the voice behind the answer and inspire the human being behind the student.
Dr. Brotati Chakraborty, Assistant Professor & Head of the Department, Department of Education, School of Education, Adamas University
Dr. Prasanta Gayen, Assistant Professor, Department of Education, School of Education, Adamas University
