The classroom hasn’t changed much in over a century. A teacher at the front, rows of students listening, and a curriculum defined by what’s testable – not necessarily what’s meaningful. But AI, as arguably the most powerful tool humanity has created in the last few years, is about to break that model open. Not with smarter software or faster grading, but by forcing us to ask: “What is the purpose of education in a world where machines could teach?” At AI News, rather than speculate about distant futures or lean on product announcements and edtech deals, we started a conversation – with an AI. We asked it what it sees when it looks at the classroom, the teacher, and the learner. What follows is a distilled version of that exchange, given here not as a technical analysis, but as a provocation. The system cracks Education is under pressure worldwide: Teachers are overworked, students are disengaged, and curricula feel outdated in a changing world. Into this comes AI – not as a patch or plug-in, but as a potential accelerant. Our opening prompt: “What roles might an AI play in education?“ The answer was wide-ranging: Personalised learning pathways Intelligent tutoring systems Administrative efficiency Language translation and accessibility tools Behavioural and emotional recognition Scalable, always-available content delivery These are features of an education system, its nuts and bolts. But what about meaning and ethics? Flawed by design? One concern kept resurfacing: bias. We asked the AI: “If you’re trained on the internet – and the internet is the output of biased, flawed human thought – doesn’t that mean your responses are equally flawed?” The AI acknowledged the logic. Bias is inherited. Inaccuracies, distortions, and blind spots all travel from teacher to pupil. What an AI learns, it learns from us, and it can reproduce our worst habits at vast scale. But we weren’t interested in letting human teachers off the hook either. So we asked: “Isn’t bias true of human educators too?” The AI agreed: human teachers are also shaped by the limitations of their training, culture, and experience. Both systems – AI and human – are imperfect. But only humans can reflect and care. That led us to a deeper question: if both AI and human can reproduce bias, why use AI at all? Why use AI in education? The AI outlined what it felt were its clear advantages, which seemed to be systemic, rather than revolutionary. The aspect of personalised learning intrigued us – after all, doing things fast and at scale is what software and computers are good at. We asked: “How much data is needed to personalise learning effectively?“ The answer: it varies. But at scale, it could require gigabytes or even terabytes of student data – performance, preferences, feedback, and longitudinal tracking over years. Which raises its own question: “What do we trade in terms of privacy for that precision?” A personalised or fragmented future? Putting aside the issue of whether we’re happy with student data being codified and ingested, if every student were to receive a tailored lesson plan, what happens to the shared experience of learning? Education has always been more than information. It’s about dialogue, debate, discomfort, empathy, and encounters with other minds, not just mirrored algorithms. AI can tailor a curriculum, but it can’t recreate the unpredictable alchemy of a classroom. We risk mistaking customisation for connection. “I use ChatGPT to provide more context […] to plan, structure and compose my essays.” – James, 17, Ottawa, Canada. The teacher reimagined Where does this leave the teacher? In the AI’s view: liberated. Freed from repetitive tasks and administrative overload, the teacher is able to spend more time guiding, mentoring, and cultivating important thinking. But this requires a shift in mindset – from delivering knowledge to curating wisdom. In broad terms, from part-time administrator, part-time teacher, to in-classroom collaborator. AI won’t replace teachers, but it might reveal which parts of the teaching job were never the most important. “The main way I use ChatGPT is to either help with ideas for when I am planning an essay, or to reinforce understanding when revising.” – Emily, 16, Eastbourne College, UK. What we teach next So, what do we want students to learn? In an AI-rich world, important thinking, ethical reasoning, and emotional intelligence rise in value. Ironically, the more intelligent our machines become, the more we’ll need to double down on what makes us human. Perhaps the ultimate lesson isn’t in what AI can teach us – but in what it can’t, or what it shouldn’t even try. Conclusion The future of education won’t be built by AI alone. The is our opportunity to modernise classrooms, and to reimagine them. Not to fear the machine, but to ask the bigger question: “What is learning in a world where all knowledge is available?” Whatever the answer is – that’s how we should be teaching next. (Image source: “Large lecture college classes” by Kevin Dooley is licensed under CC BY 2.0) See also: AI in education: Balancing promises and pitfalls Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo. Explore other upcoming enterprise technology events and webinars powered by TechForge here.