If AI removes the routine work through which novices once developed judgement, universities must deliberately rebuild the practice, feedback and accountable performance that make expertise possible.
As access to increasingly capable AI becomes widespread, sustainable advantage depends less on owning better models and more on how organisations redesign work around them.
Agentic AI moves the challenge beyond prompting. People increasingly need to know what to delegate, how to supervise execution, when to intervene and how to remain accountable.
Higher education must prepare students not simply to use AI, but to perform the forms of cognitive work that become more valuable when routine production can be delegated.
Knowing how to operate AI is not the same as being prepared to work intelligently with it. Judgement, reasoning and responsibility are becoming the more important educational problem.
AI may dramatically expand productive capacity, but its social value will depend on whether education, organisations and policy evolve beyond assumptions built around yesterday's jobs and tasks.
AI compresses the value of routine competence while increasing the leverage available to people with specialised knowledge, judgement and adaptive expertise.
Prompting becomes educationally meaningful when it helps students formulate problems, expose assumptions and iteratively improve reasoning — not merely obtain better outputs.
The important question is not whether AI performs cognitive work for us, but which forms of offloading weaken capability and which forms create genuine cognitive augmentation.
Generative AI can make active learning more responsive through Socratic dialogue, rapid feedback and personalised exploration — if classroom design keeps students cognitively engaged.
When content production becomes abundant, education must shift from reproducing information toward interpretation, synthesis, judgement and the intelligent application of knowledge.
The most valuable AI systems may not be those that simply complete tasks, but those that help people examine problems, generate alternatives and think more effectively.
Fluent AI makes rapid answers easier. Education therefore has an even stronger reason to cultivate deliberate analysis, scepticism, evidence evaluation and reflection.
AI literacy should be built around responsible use, critical evaluation and structured thinking rather than reduced to technical familiarity with current tools.