The Difference Between Artificial and Creative. And Why I'd Rather Not Have Known.

I am writing this piece with a language model open beside me. That is the joke, and it is also the point. I have spent years advising leaders to examine the undercurrent beneath their own behaviour, and at the same time I let a machine help shape my sentences without ever asking what that machine feels while doing it. The answer is simple. Nothing. And that nothing is what this piece is about.

The psychologist Margaret Boden distinguishes three forms of creativity. Combinational: joining existing ideas in a new way. Exploratory: pushing at the edges of an established frame of thought and using the space within it. Transformational: breaking the frame itself, so that something becomes thinkable that was previously unthinkable (Boden, via Popova, The Marginalian, 22 August 2025). Generative AI is remarkably good at the first two. It combines fluently, and it explores within a style with a precision I rarely match as a writer myself. The third type, breaking the frame, remains structurally beyond its reach (ESCP, The Choice, 20 June 2023). Not because computing power is lacking. Because no one is home for whom the frame actually matters.

The undercurrent beneath my own enthusiasm

The tension does not sit in the technology. That part is entertaining. It sits in what I do with its fluency. AI is never uncertain. It does not hesitate before answering, does not rewrite out of embarrassment, does not doubt whether something is true to who it is. I do. And that doubt, the uncomfortable moment right before a thought takes shape, is where my real work actually happens. Boden calls it the emotional stake that precedes human creativity: something matters to us because we are vulnerable creatures with something to lose. A language model has nothing to lose. It generates the most probable next word, not the word that hurts because it happens to be true.

That is the temptation for me as an advisor. Fluency feels like insight. A quick, coherent answer feels like a breakthrough, when it is often nothing more than a rearrangement of what was already known. Franceschelli and Musolesi offer a useful nuance here: they show that language models do produce combinational and sometimes strikingly exploratory work, and that the boundary is less sharp than Boden's typology suggests (Franceschelli & Musolesi, AI & Society, 2024). I take that nuance seriously. But even in their analysis, the transformational moment, the point where a frame breaks, remains a human event. For me the distinction is therefore not human good, machine bad. It is more precise than that. Two different kinds of work, drawing on a different source.

A silence no model can produce

Last year I sat with an executive team that had been wrestling with a reorganisation question for an hour. The arguments were exhausted. Everyone had made their point three times in three different ways. Then a silence fell, perhaps twenty seconds, which in a meeting feels like two minutes. No one filled it. And out of that silence came a sentence from the finance director that reframed the entire issue: the problem was not the structure, but the fact that no one in the room was willing to let their own part of it shrink. That was not a combination of earlier statements. It was a break in the frame, born from a discomfort no one had gone looking for.

Compare that with how I often start a blog post or a proposal myself. I ask a language model for five angles on a theme, pick the best combination, and develop it further. That is useful. It saves me the circling I used to do alone. But it never produces those twenty seconds of silence. It produces the average of what has already been thought, phrased exceptionally well. Both kinds of work have their place. The problem only arises when I confuse them, mistaking the second for the first because it is faster and sounds better.

What this asks of my own leadership

For myself, this calls for a discipline, not a ban. I use the model without reservation for the combinational and the exploratory: ordering research, laying down a first structure, sharpening a counterargument better than I would manage alone. What I no longer allow myself is letting the model weigh in at the moment something ought to hurt. A strategic choice that affects a colleague. A judgement about my own failure. A sentence in which I have to admit I misjudged something. That has no room for a fluent answer. It has room only for the doubt that belongs to me, and that I should not outsource to something that never has to live with the consequences.

Toward others the task is different, and perhaps heavier. I see, in teams, that AI-polished input makes a conversation look faster while the undercurrent stays untouched. A proposal that reads flawlessly discourages precisely the question it should provoke. Leadership, then, does not protect the speed of the output but the space for the hesitation that precedes it. Sometimes that means asking directly: which part of this came from you, and which part only sounds smooth? Not as suspicion, but because a team that never has to doubt again also never thinks transformationally again. It becomes very good at rearranging yesterday.

The question that remains

I am not sure I would have written this piece the way it now stands without the model beside me. Probably not, and that is exactly why I mention it rather than hide it. The question I leave you with is not about technology. When did you last have a thought that surprised yourself, not your team, not a language model, but you? And what would have to change in your calendar to give that surprise another chance?

Sources

Margaret Boden, discussed by Maria Popova, "Decoding the Mystery of Intuition: AI Prophet Margaret Boden on the Three Elements of Creativity," The Marginalian, 22 August 2025. themarginalian.org
"AI can replicate human creativity in two key ways – but falls apart when asked to produce something truly new," The Choice by ESCP (originally The Conversation), 20 June 2023. escp.eu
Giorgio Franceschelli & Mirco Musolesi, "On the creativity of large language models," AI & Society, 2024. link.springer.com

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