This page brings together a selection of resources to help explore how education systems might evolve in the age of AI. The resources are organised around six key “levers” from our theoretical framework — areas where artificial intelligence is already beginning to reshape education, including what students learn, how teachers teach, and how education systems operate. The six key levers are arranged across three horizons of change, the Upgrades of today, the Disruptions of tomorrow, and the Transformations of the future.
Theoretical Framework
These materials complement the Theoretical Framework Cards exercise used in several recent workshops by the AI Observatory. The exercise helps participants map and discuss how AI may influence different parts of the education system. The cards will be made publicly available soon.
Lever 1: Enable Learners
Personalised, adaptive learning and future-ready skills.
Creating enabled learners means equipping them with technical literacy and the human skills to thrive in a world still taking shape. Enabled learners are not passive consumers of AI. They are curious, adaptive, and critically engaged – with uniquely human creativity and judgment.
Upgrade
How do you shape AI as a tool for critical thinking and creativity – not just an answer machine?
Disrupt
How might you reform curricula to help students collaborate, solve problems, and effectively use AI in their lives and careers?
Transform
How do you ensure learners can not only use AI — but question, shape, and co-create with it?
Lever 2: Empower Teachers
More time and headspace for teaching and supporting students.
Empowered teachers are co-designers of how AI enters their classrooms — with the agency to put student outcomes first. The vision: teachers and AI in genuine collaboration, extending human cognition rather than replacing it.
Upgrade
How might you support teachers with training and guardrails to shift from uncertainty to confidence in using AI effectively?
Disrupt
How do you co-design AI tools and policies with teachers so they reflect real teaching and learning needs?
Transform
How might AI help teachers build more engaging, adaptive learning experiences — ensuring no student is left behind?
Lever 3: Streamline Bureaucracy
Smarter planning, faster responses, smoother systems.
AI offers an overlooked frontier: making the administrative systems that support education, smarter and more effective. Streamlined bureaucracy means simplifying procedures, accelerating resource allocation, and freeing up capacity across the system. Ministries face pressure to do more with less — AI can help, but only if it builds trust and keeps human values central.
Upgrade
How might AI make school management and processes more efficient — without sacrificing accountability?
Disrupt
Which “behind the scenes” tasks at every level of your education system could AI optimise — and where should it not?
Transform
How might you connect and automate governance to overcome capacity gaps while keeping human oversight central?
Lever 4: Align Partnerships
Private and public actors coordinated around learning outcomes.
Realising AI’s potential requires more than good technology — it demands purposeful collaboration. Aligned partnerships mean governments engaging with industry on their own terms, backed by strong oversight and sustained multi-stakeholder collaboration. As Big Tech expands in LMICs, governments face a real risk of ceding control over decisions that should be shaped by public interest.
Upgrade
How might you create policies and programmes that enable AI in education while protecting learners and national education system priorities?
Disrupt
How do you move from one-off partnerships to structured, long-term alliances between governments, industry, and academia?
Transform
How might you build open, decentralised networks for learning in the age of AI that reduces dependency on any single tech provider?
Lever 5: Context-Driven Solutions
Tech shaped around local needs, not the other way round.
Too often, AI tools are built elsewhere and dropped in without regard for local realities. Context-driven solutions flip this dynamic – ensuring AI is shaped by the needs, languages, and constraints of the people and places it serves. This means locally attuned models, trained using local data, customs and languages, and overlooked communities included in AI governance.
Upgrade
How do you ensure AI tools align with your local curriculum, assessment, and teacher needs — rather than overriding them?
Disrupt
How might you co-design solutions that reflect local education priorities, languages, and ethics?
Transform
How could your context leapfrog the global status quo and create education models built for — not borrowed from — elsewhere?
Lever 6: Renew the Purpose of Learning
Rethinking what education is for in the AI age.
In a world shaped by AI, education faces a fundamental question: what is learning actually for? This lever means going beyond using AI to replicate existing systems faster — and asking how it can help more learners achieve more, more equitably. From widening access for out-of-school youth to reimagining long-term goals — this is about values, not just efficiency.
Upgrade
How might you use AI to enhance learning outcomes for all — including learners with disabilities and those out of school?
Disrupt
How do you plan intentionally for AI to drive long-term learning improvements, not just short-term efficiency gains?
Transform
How might you reimagine the purpose of education in the AI age — with the foresight to do things differently from previous technology waves?
