There’s a familiar kind of panic that happens when a new technology arrives—one that feels like it threatens something uniquely human. We saw it when photography emerged—surely painting was over. When synthesisers arrived—real musicianship was doomed. And now, here we are with AI, having the same debate over creativity.
But if we are so deeply afraid of losing our edge, our ingenuity, our creative humanity, we have to first agree on what it is that we are losing. We need a sober thought for what human creativity actually is.
I quite like Margaret Boden’s seminal take on human creativity: it comes in three forms.
Combinational.
Explorational.
Transformational.
In her telling, Combinational Creativity is when we smash two unrelated things together and watch something weird and wonderful emerge. Think fusion cuisine, Barbenheimer, or, one could argue, AI-generated love poems.
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Explorational Creativity takes an existing playbook and pushes its boundaries. This is jazz improvisation, genre-bending films, or iterative tech innovations—new, but within familiar rules.
And Transformational Creativity breaks the system altogether. It rewrites the rules without apology. This is Einstein’s relativity, Picasso’s cubism, or the first viral TikTok that made no sense—until suddenly, it did.
It would be comforting for me to make sweeping statements to justify our human exceptionalism—that AI cannot possibly do what human creativity does—but I regret to admit what I find closer to the truth: when you break it down into these neat little packages, this mystical concept of creativity that we all refer to but can’t really picture in our mind’s eye, existing just beyond the grasp of what we can hold, is actually pretty straightforward. We can wrap our arms around it. It’s unsettlingly simple.
If creativity is all about where you’re working—within the lines, at the edges, or tearing up the whole canvas—then we can all agree that today, our generative AI models practice almost exclusively combinational creativity, perhaps even some prompted explorational, but not (yet) transformational.
That’s the thing about generative AI. It’s generative, sure—but that also means it’s profoundly generic. It can remix, refine, extrapolate. But it doesn’t invent. Today, AI cannot decide to break the rules. It won’t introduce contradiction, subtext, or tension—the very human things that make great art, great writing, and great ideas. It refines the past. It does not invent the future.
Right now, our generative AI models are built to predict the most statistically probable next word, next brushstroke, next note. They are trained on what already exists. By definition, they produce creative work that is completely average. They cannot make the leap. Not yet. And certainly not on their own.
Generative AI is remixing the statistical mean of human output. It is, by design, a machine of consensus. And consensus does not create breakthroughs.
For AI to go from remixing to reinventing, it would need not just data, not only prompts, but actual intention—the ability to set its own objectives. And that’s where the real inflection point lies.
But if there’s anything we know about the pace of change, it’s that it happens in “two ways: Gradually, then suddenly.” (Hemingway).
Some might say we’ve just hit “suddenly.”
As we “suddenly” enter an age of AGI and Agentic Intelligence, we can expect models that can achieve genuine innovation and self-directed breakthroughs—we can expect transformational creativity.
This raises the question: if the outer limits of our human creativity have actually been the inner limits of our lived experience as individuals, then there is every possibility that when the entire lexicon of human history, art, knowledge, and experience is consumed and drawn from as a resource for a roaring agentic engine, explorational and transformational creativity could very well cure cancer, reverse climate change, or calculate where to find life off Earth.
What excites me—and I say this as someone who invests in technology—is the sense that AI is poised to become a great enabler of creativity rather than its undoing. Think about open-source software: the entire philosophy is that when we put our code—our ideas—out in the world, others build on them. You see that same pattern in every artistic revolution. No Picasso without African masks. No Basquiat without Warhol. No Kendrick Lamar without Gil Scott-Heron. We’ve always borrowed, remixed, adapted. Creativity was never about ownership. It was (and is) about humans combining unexpected elements to push the boundaries of what exists. AI can’t (yet) the truly weird or wonderful stuff all on its own. But it can help us refine our own leaps of imagination—if we’re bold enough to spark them in the first place.
And that’s why human creativity remains the definitive advantage. As AI tools become ubiquitous and technically competent, they’ll compete on price and efficiency. This means the differentiator—the thing that creates actual value—is not the tool. It’s the thinking behind it. The ideas.
The Great Flattening—You Can’t Teach Taste (But You Can Lose It)
If you’ve recently noticed that everything feels the same, it’s because we’ve been trending towards sameness for years.
We used to dig through record stores for new releases, burn mixtapes for lovers, and meticulously curate playlists with layers of innuendo. We made choices. We had opinions. Today, we’re drip-fed Lo-Fi Beats through an IV of Discover Weekly on Spotify. TikTok serves up micro-trends so fast that novelty collapses into noise. Netflix auto-plays the next best thing before we’ve even decided if we liked the first. Anything to reduce the cognitive load.
Because taste requires effort. The effort to choose. To interrogate. To reject what doesn’t resonate and lean fully into what does. But frictionless consumption has made us so very lazy. We don’t build taste anymore. We outsource it to recommendation engines.
And when we stop making active choices, we stop knowing what we actually like. If everyone has access to the same AI, the competitive advantage shifts from who has the best tech to who has the best taste. But taste isn’t just about aesthetic sensibility. It’s about the ability to interrogate ideas, to recognize quality, to know when something is actually good. Taste is mission-critical.
This is why AI feels threatening—if we’ve spent the past decade letting algorithms shape our preferences, what’s left of our own instincts?
The Cost of Creativity
Here’s the good news: if AI floods the market with low-quality, auto-generated “slop,” then human creativity just became more valuable. The invention of the camera didn’t kill painting. It killed mediocre painting. It forced artists to push past realism into abstraction, surrealism, cubism—to find new ways of seeing our world.
Those who thrive in this new world won’t be the ones obsessing over detailed prompts, tweaking GPT settings for marginally better output. It will be the ones who have something real to say going in. Something weird. Something unexpected. Something imperfect and original and unmistakably not the statistical mean. And no machine will ever do that for you.
First Principles
There’s an old saying in venture capital: “Bet on the jockey, not the horse.” The idea being that a startup’s success hinges more on the founder’s vision and execution than the technology they’re building. It’s a sentiment that feels increasingly relevant in this moment of AI acceleration, where the tools are rapidly becoming democratised and ubiquitous.
As technology becomes the commodity, powerful, bold, courageous ideas and discerning taste become the real leverage point for value.
Outlier founders and companies will be those who identify real human problems to solve and uncover ingenious, transformational ways to solve them.
Equally critical for investors, in a moment where new AI start ups are minted by the minute, your taste becomes your compass in navigating this paradox of choice. Taste is your instinct for what cuts through and may potentially hold real future value—so honing it isn’t optional, it’s essential.
Generative models today are inherently divergent. They spit out endless iterations of possible solutions, each no more unique or differentiated than the last. It’s up to us, as humans, to be convergent. Creativity is not about volume or efficiency. It’s about making choices. Choosing the right problems to solve. And solving them in the right way.
This is where AI won’t (and can’t) help. It can generate infinite variations. But it won’t tell you which ones matter.
That’s a human decision.
That’s up to you.
Contributed to Branding Strategy Insider by Elli Hanson, Principal Investor at Side Stage Ventures.
At The Blake Project, we help clients worldwide, in all stages of development, define and articulate what makes them competitive and valuable at pivotal moments of change. Please email us to learn how we can help you compete differently.
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