If we teach today as we taught yesterday, we rob our children of tomorrow. — John Dewey
It was a late afternoon when I descended the stairs from the sixth floor. Walking past the landing, I noticed a small group of students gathered near the railings, intently working on something. A glance at their screens, followed by a deliberate act of pretending not to see, revealed that they were using ChatGPT to work on the company valuation assignment I had handed out that morning as part of an elective course.
As I had suspected, many students came prepared with detailed solutions the next day. Interestingly, they had created multiple scenarios with different valuation outcomes. Several were ready for my questions and could anticipate and respond before I finished asking. I couldn’t help but reflect on how different this was from my own postgraduate and doctoral days, when take-home assignments and exams felt daunting and intellectually demanding. Back then, we feared the complexity of such tasks. Now, with tools like ChatGPT, the academic landscape has changed. Unless an instructor makes substantial effort to craft questions that artificial intelligence (AI) cannot easily answer, traditional assessment methods may no longer be effective.
A week later, a colleague shared a similar story. She had given her students a month to complete a marketing project, only to find that many had finished it in two weeks. Not only had they completed the content, but they had also conducted statistical analyses and presented meaningful interpretations, tasks that once posed significant challenges. Even a senior academic administrator with a background in computer science expressed his concerns. He noted that students often bypass the foundational steps of learning to code, relying instead on AI-generated solutions. The gaps become evident during interviews, where some students struggle to explain core concepts or the logic behind their code.
We are now teaching a generation born between 1995 and 2009, commonly referred to as Generation Z. This is a globally connected generation shaped by the digital world and social media. The challenge is no longer whether AI will influence education; it already has. The real question is how educators from earlier generations, Baby Boomers, Generation X, and Millennials like myself, can effectively teach students from Generation Z and, soon, Generation Alpha.
Before discussing AI’s role in education, let me clarify the term. As often attributed to Voltaire, “If you wish to converse with me, define your terms.” Artificial intelligence generally refers to computer systems that can carry out functions typically associated with human thinking. These may include learning from data, reasoning, problem-solving, language understanding, pattern recognition, and decision-making. Examples include smart assistants like Siri and Alexa, and generative AI tools like Copilot, Gemini, and ChatGPT.
Let me begin by acknowledging the many ways AI can benefit today’s students. As a student myself, one of the most liberating aspects of AI was the ability to ask questions without fear or embarrassment. During school, we were encouraged to ask questions, but not always without judgment. There was a well-known quote: “A man ashamed of asking is afraid of learning.” Yet in practice, asking what were seen as simple questions often resulted in eye-rolls or reprimands. With AI, however, no question is too basic.
Whether it’s something out of a movie like “What is theta in sin theta?” or “Is a tomato a fruit or a vegetable?”, AI responds with patience and clarity. Unlike a typical teacher or professor who might frown or dismiss you, AI provides straightforward and courteous explanations. Another related advantage is that AI doesn’t get exhausted or irritated, even if students ask the same doubt multiple times or struggle to understand its explanations. In contrast, in a typical teacher-student exchange, repeated questions or confusion can sometimes lead to frustration or impatience from the instructor.
With AI, students can persist in seeking clarity without worrying about how their intellectual capabilities might be judged. This creates a more relaxed and focused learning environment, where the emphasis remains on understanding the concept rather than managing social dynamics. Second, AI often provides step-by-step guidance. When used alongside textbooks and class materials, it helps students identify where they are struggling and what needs reinforcement. This kind of personalised attention is difficult in classrooms where one teacher manages many learners.
From self-quizzing and study guides to supplementary tutoring, AI offers individualised support to improve understanding and outcomes. What makes this support even more powerful is AI’s ability to build and adapt based on each learner’s unique profile. With appropriate data safeguards, AI can track a student’s strengths and areas of difficulty over time. For instance, if a student consistently struggles with integrals, the system can deliver targeted conceptual explanations, generate focused quizzes, and even recommend revision schedules tailored to that specific need.
Teachers can also use these insights to guide interventions or modify instruction. This kind of adaptive learning boosts exam performance and encourages deeper, sustained understanding. Third, AI supports interdisciplinary learning by offering a broader and more integrated perspective than what is typically available in subject-specific classrooms. A math teacher, for instance, may focus on teaching differentiation within the confines of mathematical theory, without necessarily showing how it connects to real-world applications or other fields.
In contrast, AI, trained on vast and varied knowledge bases, can draw meaningful links between mathematical concepts and their relevance in disciplines such as physics, economics, environmental science, or even digital design. This cross-disciplinary ability helps students appreciate the broader utility of what they are learning. Moreover, it nurtures a deeper intellectual curiosity by enabling students to explore how foundational ideas manifest across fields and geographies. Take literature, for example, AI can explain how the Renaissance movement shaped literary traditions across different cultures, revealing both common threads and cultural divergences.
By situating subject knowledge in a broader global and disciplinary context, AI encourages learners to see education not as isolated silos but as an interconnected web of ideas. Fourth, AI helps bridge language and other technical barriers, making education more inclusive and accessible. This is particularly valuable in a multilingual country like India, where many students face challenges related to pronunciation, comprehension, or simply gaining confidence when learning in a non-native language.
AI tools, equipped with multilingual capabilities, can interpret, translate, and respond in a range of languages, allowing students to engage with content in the language they are most comfortable with. For example, text-to-audio features can convert written material into spoken content, enabling learners to listen and revise at their own pace, whether during a commute or while relaxing at home. This flexibility not only accommodates different learning styles but also supports students with visual impairments or reading difficulties. In this way, AI plays a vital role in breaking down linguistic and technical hurdles that often stand in the way of effective learning.
Fifth, and perhaps most practically, is accessibility. I’ll admit that I occasionally get frustrated when students reach out late at night. But AI doesn’t mind. It’s always available, offering round-the-clock access to educational support. This flexibility allows students to learn at their own pace, regardless of time zones or schedules, ensuring a more equitable learning environment.
Given these benefits, many universities abroad have already begun integrating AI in structured ways. The University of Plymouth, for example, provides clear guidance on how students can use AI tools for learning. These include creating study schedules, preparing for group assessments, building revision materials, translating content, defining complex concepts, and generating writing ideas. These practices represent a significant shift in educational methods. AI is transforming how we teach, learn, and interact in the classroom.
As Arvind Narayanan and Sayash Kapoor note in their book AI Snake Oil, AI is not a threat to education any more than the calculator once was. With appropriate oversight and thoughtful use, AI can be a powerful partner in learning. But to fully harness its potential, educators like me must rethink the curriculum, redesign assessments, and reflect on what meaningful learning really looks like. Many educators are already embracing AI in innovative ways. For instance, a Substack newsletter called ChatGPT for Education highlights the work of thirty pioneering teachers who use AI creatively in their classrooms.
One such educator employs ChatGPT to facilitate role-playing exercises with famous philosophers. Through AI-generated simulations based on historical writings and ideas, students can engage in debates that present contrasting viewpoints and explore diverse perspectives on complex issues. This method deepens learners’ understanding of key principles, as well as the strengths and weaknesses of different doctrines, by bringing them to life in realistic scenarios. Another educator uses AI to create customised practice problems for statistics students, offering tailored challenges that adapt to individual learning needs. This kind of personalisation and innovation was previously difficult to implement on a large scale.
To put it in perspective, when I was a student, we had to imagine elements like sodium and chloride sitting in beakers to answer theoretical questions, often without access to the actual materials. Today, AI allows students to visualise, simulate, and interact with such scenarios directly. The classroom has evolved beyond whiteboards and textbooks to become a dynamic, AI-enhanced learning environment. As an instructor, I have come to accept a humbling truth. If I fail to offer a clear explanation, my students can now turn to an AI tutor who might do a better job.
This doesn’t make me less relevant; it makes my role even more vital. I must guide students not only on what to learn but also on how to learn, ask effective questions, and evaluate the answers AI provides critically. Recently, some have argued that educators, using AI, should emphasise the learning process over simply grading outcomes, focusing on, say, the creation of an essay rather than just the final product. As Professor Mitchell Petersen of Kellogg observes, facts are now abundant and easily accessible, so teaching has shifted from simply sharing information to providing meaningful context.
With students bringing vast knowledge, instructors orchestrate how to combine the students’ insights with their own. AI can facilitate this orchestration by assembling diverse information into a coherent structure. As the world increasingly embraces AI across fields like medicine, engineering, defence, anthropology, and genetics, its relevance in education is no longer in question. Employers today actively seek individuals who are comfortable using AI tools and can adapt to technology-driven environments. According to Nvidia CEO Jensen Huang, using AI is about asking the right questions.
He observes that the future will reward critical thinkers who collaborate with machines, not just those who memorise facts. In this context, dismissing AI without understanding its potential benefits can be short-sighted. As one of my academic colleagues aptly put it, whether you’re an instructor or a student, your knowledge today is increasingly shaped by your ability to search effectively through traditional means like Google and newer tools powered by AI. It’s no surprise that even schools are beginning to integrate AI into classrooms, recognising its value in enhancing teaching and learning. In particular, generative models can potentially transform personalised learning and assessment meaningfully.
Like any powerful technology, AI comes with limitations and challenges. These concerns deserve attention, though fully exploring them requires more space and time than I have here. That is a conversation for another day. Before I sign off, a brief declaration aligned with a key principle of AI transparency: After drafting and refining this piece through my usual edits, I turned to ChatGPT to help streamline the structure and ensure clarity. It confirmed that the content flows smoothly, is engaging, and is ready as an opinion piece.
So if you’ve read this far, you know that this article results from a thoughtful collaboration between human intent and AI assistance.
* The views expressed in this article are his own and do not reflect those of the institute, which is mentioned solely for identification purposes.
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