James Barton, Global Director of MPW Group, on why AI is a powerful and positive force in education, but always in a supporting role
Would Shakespeare have been more or less powerful with an AI co-pilot? Would his output have multiplied, or would the poetry have thinned? To prompt or not to prompt is not the point – the question is whether the tool serves learning or takes over.
From the Jacquard loom to Babbage and Lovelace, from Mary Shelley’s laboratory to Turing’s conversational test, we’ve seen radical technologies since before the Bard. In education it feels novel because the AI rollout is happening now. The present twist is scale. Large language models can draft, summarise and simulate at speed.
The parental voice of concern is justifiable. If a machine performs the heavy lifting, does our own intelligence slacken? Struggle is part of learning and the temptation to outsource that struggle is real. Institutions harbour their own fears. What if AI becomes so fluent that erroneous or inauthentic submissions slip past detection, eroding trust in assessment? These risks are not imaginary but call for design, not drama.
Education is not the efficient production of tidy answers, but the formation of curiosity, integrity and judgement. Keep that in view and AI remains a tool, and even a co-pilot, but not the tutor. Ring-fence its use through transparent prompts, declared outputs and clear limits. Build assessments that prize process as well as end product – more in-class writing, viva-style orals, iterative portfolios and applied tasks that require students to show their working as well as their results. Good design makes misuse harder and learning stickier.
Used well, AI is genuine value-added. In secondary schools, it can generate retrieval practice, adapt reading levels and offer immediate, low-stakes feedback. For pupils learning in another language, it can clarify instructions without lowering the bar. In universities, it can annotate articles, propose code comments, draft lab pre-work and produce alternative explanations for stubborn concepts. Think of AI as rehearsal room – a place to try an argument, hear it back and refine it before the performance that counts.
AI will certainly replace tasks. Marking routine quizzes, preparing differentiated materials and providing first-pass feedback are jobs machines already handle well. But no model reads a room and spots the student who hides brilliance behind quietness or turns a near-miss into an ‘aha’ moment. This means the teacher role shifts from solo lecturer to conductor of attention and designer of practice – teacher-led, now tool-enabled. Prospero keeps command of the stage not because he owns the book but because he understands the play.
In the workplace, large firms now deploy secure, white-labelled models to cut drudgery and raise quality. Graduates will meet such systems on day one. Failing to teach AI literacy would leave them under-prepared. If Shakespeare had an AI co-pilot, the task would still be his – he would choose the question, test the line and own the judgement.
At MPW we learned during the pandemic that technology can preserve momentum, but teachers sustain learning. That lesson now shapes a clear approach. We use AI where it demonstrably adds value – personalising practice, widening timely feedback and supporting EAL learners – while keeping authorship, fairness and the teacher-student relationship at the centre. Tools extend us, teachers transform us. Keep the craft in charge and Shakespeare’s co-pilot earns a seat but not the quill.
MPW mpw.ac.uk
Further reading: Queen Ethelburga’s on intelligence thinking
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