The New Learning: From Learning to Knowing in the age of AI

On the dangers of outsourcing thought in the age of AI

I was wondering… as another academic year begins and the familiar rituals of learning return - teachers preparing, students arriving, families anticipating - what kind of learning will truly prepare us for the age we’re stepping into?

We once placed our hopes in so-called “future-proof” skills: coding, robotics, data literacy, design thinking. Yet already, these too are being outpaced by machines. What we thought of as anchors for the future are proving temporary, if not obsolete - scaffolds dismantled almost as quickly as they are built. If the skills we once trusted to secure the future are already being overtaken, then what, truly, is worth teaching?

This is the unsettling truth we must face: we are at risk of outsourcing not just our labor, but our very cognition. Step by step, we are handing over our capacity to reason, to remember and synthesise. AI drafts our words, summarises our readings, and produces answers before we have even formed the question. What remains for us to do?...To skim? To approve? To consume? To trust blindly?

This is not learning that produces comprehension, understanding, and true Knowing. It is simulated knowing - quick, easy, disposable. It feels like knowing more, but in truth we are remembering less, imagining less, becoming less - and this is eroding our ability to apply and use knowledge in meaningful ways and in different contexts.

Among students, AI is no longer a novelty - it is embedded in their academic lives. A 2025 global survey found that 86% of students use AI in their studies, with over half using it weekly, and nearly a quarter using it daily. In the UK, 92% of undergraduates report using generative AI tools in their coursework, up from 66% just a year prior. The pace of this adoption should make us pause and reflect. What kind of learners are we shaping if the default is not to think first, but to offload without thinking?

AI can certainly support learning. But what it gives in convenience, it takes from endurance. Heavy dependence risks hollowing out the essence of learning itself: the slow and sometimes difficult work of questioning, wrestling with different ideas, carrying them long enough for them to become part of us. If machines bear that weight, what remains for us to carry?

We may feel as if we know more, because more is at our fingertips. But what of it truly becomes us? How much of this knowing is translated into Being, into Doing? How much dissolves back into noise?

This is the danger of cognitive outsourcing. If we allow machines to carry the weight of connecting, reconfiguring, and questions, our own capacity for thinking risks atrophy. Just as muscles weaken when unused, so too does the human mind. And if this becomes the inheritance we pass on, the next generation may inherit powerful tools without the discernment to wield them wisely.

So as this new academic year begins, perhaps the question we need to ask ourselves as educators is this: how should New Learning look in the age of AI? Not only what and how the students should be learning - but also why. The old “why” was often about preparing for a first job. But in the age of AI, the “why” must go deeper: it is about cultivating creative adaptability, the ability to reconfigure, to think for ourselves, and to carry wonder and meaning in a world where machines can carry almost everything else. Perhaps the real shift is this: to measure learning less by how quickly we find an answer, and more by what endures in us once the answers are found. And if that is the case, then what might we begin to model differently, for our children, our students and for our world?

• Cultivate curiosity before certainty. When children or students ask, resist the impulse to rush to an answer - human or machine. Sit with the question. Explore it alone and together. Show that learning begins in wonder, not in instant conclusions.
• Reveal the process, not just the result. Let them see you wrestle with a passage, puzzle through a problem, or revise a thought. It teaches that patience and struggle are not signs of weakness, but the very soil where Knowing takes root.
• Use AI as a companion, not a compass. Let it walk alongside you but never dictating the direction of thought. Encourage students to treat AI as a beginning, not an end: compare and validate its answers, question its gaps, build upon its suggestions. Show that tools can support thinking, but never replace the act of thinking for ourselves.

​​The truth is this: in the age of AI, we do not need more answers. We need the resilience to keep asking better questions, and the wisdom to know what is worth carrying. Knowledge Mindfulness reminds us that “Knowing” is not something we outsource, but a living system - a kind of intangible energy embedded in mind, heart, body, and soul.So I wonder: what do we most need to pass on? Not skills that may vanish in no time, but the courage to see clearly, the commitment to know deeply,, and the capacity to lead our own thinking - to remain fully human in a time when machines can do almost everything else. What we choose to take in, and how we let it shape us, may be the truest form of “Knowing” we have left.

With care for “All,”

Dr Laila Marouf and the KMD team