The end of term often arrives with a mixture of exhaustion and relief. Marking piles shrink, inboxes quieten, and for a short while, your time is more your own. That makes the holidays an unusually good moment for AI‑focused CPD: enough distance from daily pressures to think strategically, but close enough to the next term that ideas still feel relevant.
AI in education is moving quickly, and it can be hard to keep up during the rush of lessons, meetings and duties. A small, well‑chosen stack of books gives you space to think deeply, connect ideas and decide what actually matters for your pupils and colleagues. Think of this guide as a holiday “menu”: a set of pathways you can follow at your own pace, with each title linked to concrete actions you can try in January.
If you are newer to AI, you might also like to pair this list with an overview of why AI literacy matters in schools in the first place, such as this guide.
This is not a list to read from top to bottom in order. Instead, treat it as a pick‑and‑mix CPD plan:
Choose one “core foundations” book to give you a shared language and big‑picture understanding.
Then pick one book aligned with your main role: classroom teacher, middle or senior leader, SENDCo, or tech/data lead.
If you have energy left, add one short read or podcast from the final section for a lighter option.
For each book, you will find:
You do not need to finish every book to benefit. Many of the January actions can be done after a few focused chapters.
Recommended title: “The AI Classroom: The Ultimate Guide to Artificial Intelligence in Education” – Daniel Fitzpatrick, Amanda Fox, Brad Weinstein
Best for: Teachers and leaders at any level who want a practical, classroom‑centred overview.
Why it matters: This book avoids hype and focuses on what AI actually looks like in lessons, planning and assessment. It covers prompt design, lesson ideas and ethical considerations in accessible language, making it a strong shared starting point for a staffroom conversation.
Try this in January: Choose one unit you are teaching in the first half‑term. Use an AI tool to generate three variations of a lesson: one for consolidation, one for stretch, one for retrieval practice. Adapt them for your context, then teach at least one. Afterwards, note what you kept, what you changed and what you would never use again. Bring those reflections to your next department or phase meeting.
For a more reflective, human‑centred perspective on working alongside AI, you might later pair this with ideas from the human–AI co‑pilot model.
Recommended title: “AI for Teachers: Practical Classroom Strategies” – Steve Dembo and Lainie Rowell
Best for: Classroom teachers across phases and subjects.
Why it matters: This book focuses on pedagogy first, tools second. It explores how AI can support feedback, differentiation, questioning and planning, with realistic examples rather than abstract promises.
Try this in January: Pick one routine task that drains your time – for example, writing model answers, generating practice questions, or creating exit tickets. Use an AI tool to create a first draft for one week. Your rule: you must edit every output before using it. At the end of the week, estimate how much time you saved and whether the quality was acceptable. Decide whether to keep, adapt or abandon that AI‑supported routine.
Alternative/extension title: “The AI‑Infused Classroom: Teaching in the Age of Artificial Intelligence” – Holly Clark
Best for: Teachers who already use technology confidently and want to push further.
Try this in January: Redesign one existing lesson so that pupils use AI as a thinking partner rather than a shortcut. For example, in a history lesson, ask pupils to prompt an AI to produce a flawed explanation of a cause of a conflict, then critique and correct it using success criteria. Build a short plenary discussion about when AI helped and when it misled them.
Recommended title: “Leadership and AI in Education: Policy, Practice and Possibility” – Rose Luckin and colleagues
Best for: Middle leaders, senior leaders, heads of department, and those with responsibility for teaching and learning.
Why it matters: This collection looks at AI through the lenses of strategy, accountability, ethics and school culture. It helps leaders think beyond tools towards systems, policies and professional learning.
Try this in January: Draft a one‑page “AI in our school: working principles” document. Include 3–5 statements such as “AI should support, not replace, professional judgement” or “Pupils must be taught to question AI outputs”. Share a draft with a small group of staff for feedback before taking it to a wider forum. This can seed a more formal policy later, especially if you connect it with a structured readiness review like the September AI checklist.
Complementary title: “Leading AI in Schools: A Practical Guide for School Leaders” – Al Kingsley
Best for: Senior leaders and governors/trustees.
Try this in January: Schedule a 30‑minute “AI horizon scan” item in a leadership meeting. Ask each leader to bring one concrete example from the book that relates to their area (curriculum, safeguarding, finance, community). Use these to identify two priorities: one risk to mitigate, one opportunity to explore this year.
Recommended title: “Inclusive AI in Education: Supporting Diverse Learners” – Gill Le Fevre and colleagues
Best for: SENDCos, inclusion leads, pastoral leaders and educational psychologists.
Why it matters: AI tools can both widen and close gaps. This book focuses on accessibility, assistive technologies, and the ethical use of AI with vulnerable learners, including data, consent and bias.
Try this in January: Identify one learner (or small group) who struggles with reading access to the curriculum. Trial an AI‑powered support for a single sequence of lessons – for example, text‑to‑speech with adjustable speed, AI‑generated simplified summaries, or scaffolded question sets. Collect the pupil’s perspective: did it help, frustrate or distract them? Use their feedback to decide whether to scale up, adapt or stop.
Extension title: “Artificial Intelligence and Inclusive Education” – Jeremy Knox (ed.)
Best for: Those interested in deeper ethical and philosophical questions.
Try this in January: Use one chapter as the basis for a short discussion with a colleague or small team. Frame the conversation around one question: “How do we ensure our use of AI does not unintentionally disadvantage any group of pupils?” Capture three practical safeguards you can implement this term.
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Recommended title: “AI and the Future of Learning: Expert Perspectives on Educational Data and Technology” – Pasi Sahlberg and colleagues
Best for: IT managers, data leads, digital learning leads and technically confident senior leaders.
Why it matters: This title connects AI with data governance, infrastructure and analytics, helping you think beyond individual apps towards a coherent architecture that protects staff and pupils.
Try this in January: Undertake a quick AI tools audit. List all AI‑related tools currently in use or being trialled in your school. For each, note: purpose, data flows (what is uploaded and where it goes), and whether you have a clear data‑protection position. Use insights from the book to prioritise two actions: one risk to address immediately, and one promising tool to evaluate more formally.
Complementary title: “The EdTech Evidence Gap: AI, Analytics and Impact” – Becka Curran and colleagues
Try this in January: Choose one AI‑enabled platform your school already uses. Define two measurable outcomes for this term (for example, increased retrieval practice frequency, reduced marking time). Plan how you will collect evidence against them, and share that plan with staff so they know what you are looking for and why.
For reflections on what actually happens in year one of AI adoption, you might also enjoy these practitioner stories.
Sometimes you simply do not have the energy for a full chapter. These shorter options keep you learning without demanding too much:
Try this in January: Pick one short piece and bring a single quote to your next team or department meeting. Use it as a five‑minute discussion starter: “Do we agree with this? What would this look like in our context?”
Reading alone does not change practice; deliberate follow‑up does. To turn your holiday reading into genuine CPD, keep things simple and focused.
First, choose just one idea from each book to test in the first half‑term. Write it down before term starts: what you will do, when, and how you will know if it helped. For example, “Use AI to generate weekly retrieval questions for Year 8 science, then compare quiz scores and my planning time after four weeks.”
Second, share your experiments. A ten‑minute slot in a staff, phase or department meeting can be enough. Focus on what worked, what did not, and what surprised you. This kind of grounded, practitioner‑led sharing often feels more trustworthy than glossy case studies.
Finally, remember that your AI journey is a marathon, not a sprint. A thoughtful, modest change that sticks is far more valuable than a dozen flashy experiments that vanish by February. If you want a more structured way to track your progress, you might adapt ideas from a whole‑school AI readiness checklist into your own personal plan.
To make this easier, sketch a simple one‑page checklist for your holiday reading:
Print it, tuck it inside your first book, and tick items off as you go. By the time you return in January, you will not just have read about AI in education; you will have a clear, realistic plan for using it thoughtfully in your own context.
Happy reading! The Automated Education Team
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