Before the Sydney Opera House became a landmark, it began as a set of hand-drawn sketches by an unknown Danish architect named Jørn Utzon. Before flat-pack furniture became a global success, someone had to imagine furniture that could be transported in pieces and assembled at home. Before sushi restaurants put your order on a conveyor belt, Yoshiaki Shiraishi in Osaka had to imagine a kitchen that moved instead of a queue that waited. None of it was inevitable. Each one started as a picture of something that didn't exist yet.

That's what imagination does. It's easy to file it away as simply a part of childhood, the thing you grow out of once real work starts. But every product, building, or breakthrough we now treat as obvious had to be imagined before it could be built. This raises a question for anyone who designs learning. If imagination precedes every leap from "what is" to "what could be," shouldn’t we focus more on incorporating it into learning experiences?

What would a school, or a training program, built for imagination look like?

Most education, and most corporate training, is still optimized for knowing the right answer. Right answers are easy to grade, easy to standardize, easy to put on a completion certificate. Imagination doesn't behave that way. It rewards the person who asks a strange question over the one who gives the expected answer, and that's a hard thing to build a syllabus around.

However, educational philosopher Maxine Greene argued decades ago that learning doesn't really start with "what is." It starts the moment someone asks "what could be." She also argues that imagination is also what makes empathy possible, since picturing someone else's experience draws on the same skill as picturing anything else that isn't directly in front of you.

So, imagine learning environments that treat imagining as a skill worth practicing deliberately. Classrooms would spend real time on "what if," not just "what is." Assessment would leave room for a genuinely surprising answer instead of only rewarding the one already in the answer key. And corporate training, which usually optimizes for compliance and competency, would build in space for people to picture how something completely familiar, like a process, a product, or a customer journey, could be different.

Imagination needs play

Play looks frivolous, which is probably why it's the first thing cut once a curriculum or a training agenda gets busy. But a detailed literature review from the British Council makes the opposite case. The review details how creative play is linked to cognitive flexibility, problem solving, and lateral thinking. It extends beyond children to also look at adults, examining how improvisational theatre in organizations and play cues in work meetings can enhance team creativity.

It's worth noting that Danish toy maker LEGO built an entire facilitation method, LEGO Serious Play, specifically to bring that kind of playful, hands-on thinking into strategy sessions and workplace training. And if you want a deeper dive into how people across very different fields actually practice imagination day to day, The Imagination Desk podcast, produced by Arizona State University's Center for Science and the Imagination, is a good place to start.

Imagination in the age of AI

This issue of imagination has become sharper now that generative AI is everywhere in both classrooms and corporate training. At Bon Education we review thousands of student projects a year and one pattern has become impossible to miss: some learners use AI in ways that are genuinely imaginative, pushing an idea somewhere it wouldn't otherwise have gone. Others turn in work that's technically polished but thin and derivative, the AI equivalent of coloring inside someone else's lines.

The difference is whether the AI is used with imagination, or in place of it. Decades ago, researchers Gavriel Salomon and David Perkins distinguished between the effects with a technology (what you can do while holding the tool) and the effects of a technology (the capability that stays with you when it’s gone). Using this frame, the question becomes simple: are we using AI to expand human capacity, or just as a temporary shortcut?

New research from MIT Sloan School of Management finds generative AI boosts employee creativity, but only for those who actively reflect on and adapt how they use it. A recent Forbes article called “AI Isn’t Replacing Creativity. It’s Moving It Upstream,” written by C.M. Rubin puts it more bluntly: most of what gets dismissed as "AI slop" isn't really a tool problem, it's a direction problem. As generative output floods every industry, the real scarcity isn't content, it's coherent human intention behind it.

That tracks with what shows up in a stack of student and employee work alike. AI doesn't hand anyone imagination. It amplifies whatever direction a person brings to it. Used well, it's a way to prototype more "what ifs" faster. Used passively, it's a shortcut around having to imagine anything at all, which is exactly the risk any organization rolling out AI training should be designing against.

None of this works without safety

Imagination asks people to take a risk. Every time someone floats an unusual idea, asks an odd question, or tries something that might not work, they're exposing themselves a little. If that feels dangerous, whether the room is full of students or senior stakeholders, most people just won't do it.

This is where psychological safety comes in. Research on design thinking education backs this up directly: environments built on trust and psychological safety consistently produce more creativity, better collaboration, and a stronger willingness to sit with uncertainty rather than rushing past it. Take that safety away, and you can offer all the frameworks and icebreakers you want. People will still play it safe.

Amy Edmondson’s Harvard University research shows that creating psychological safety often comes down to practical design choices. For example, being intentional about pausing judgment during brainstorming. Explicitly separating the processes of ideation (simply generating ideas) from evaluation (giving a verdict on the quality of the ideas) can give people the freedom to float unusual, high-reward ideas. Similarly, it is helpful to reframe missteps in the creative process as ‘prototype data’ rather than mistakes, shifting the focus away from judgment and toward discovery by asking: "What did this attempt teach us?"

The future isn't going to hand out a syllabus

The people learning today, whether they're students or employees, will run into problems that don't exist yet. No rulebook or onboarding deck covers challenges that haven't been discovered yet. So instead of optimizing purely for known answers, it makes more sense to help learners build the capacity to imagine alternatives, sit with uncertainty, and connect ideas across fields that don't usually talk to each other.

It's tempting to think imagination is only about art and make-believe. But picturing a new product, a new process, or a new way of solving an old problem, moving from the status quo to something that doesn't exist yet, is exactly what foresight and innovation require. You can't plan for a future you can't picture, and you can't build something new without imagining it first.