Who Made This? The Crisis and Evolution of Creative Authorship in the AI Era

There's no shortage of debate about whether AI can be creative. Can it make art? Can it be original? Can it think? These questions get asked so often they've started to feel performative, as if the very act of repeating them were a form of intellectual engagement. But the more pressing and overlooked question isn't can AI create. It's should we use it when we do? And if so, how?

This piece isn't a meditation on the soul of machines. It's an exploration of what creative integrity looks like when intelligent tools become part of the process, and what happens to us in the bargain.

When art meets application

If you're making art purely for art's sake (e.g. painting with no audience in mind, writing poetry for the sole purpose of self-expression), you can safely ignore AI. That's the realm of unfiltered personal expression. But when creative work enters an applied context (e.g. client work, commercial design, branded storytelling, content marketing, product UX), it plays by different rules.

AI is obviously changing everything, but it's not because it can replace creatives. It's because it can augment them in ways that make those who refuse to engage feel slower, less agile, and ultimately less competitive. In applied creativity, speed, iteration, and clarity matter. These aren't, I don't think, antithetical to art. They're a different form of creative excellence.

But here's what I'm starting to realize: this efficiency imperative might be reshaping the entire creative economy in ways we've not yet fully reckoned with. If an AI-assisted creative can produce three times the output in the same timeframe, what happens to the two-thirds of creatives who get priced out? We're not just talking about tool adoption. We're talking about a fundamental restructuring of creative labor.

The real threat isn't AI

There's a misconception that AI threatens creativity by producing too much content. But the problem isn't volume, it's derivativeness. Too often, what passes for insight is just recycled information presented with a veneer of originality. AI makes that easier to do. It can remix, repackage, and reframe existing ideas in a virtually endless loop.

The real danger isn't that AI will replace creativity. It's that people will stop doing the original thinking and let AI generate work that looks the part but lacks depth, specificity, and soul. The result is content that's polished but empty. Strategic but forgettable. Clean but completely soulless.

But I want to be more specific about what "original thinking" actually means, because I've been using the phrase without defining it. When I say original thinking, I mean three distinct capacities: pattern disruption (seeing where conventional wisdom breaks down), synthesis (connecting ideas across domains in unexpected ways), and judgment (knowing what matters and why). 

These are the irreducibly human contributions that no amount of AI assistance can simulate.

What I use AI for (and what it uses me for)

In my own work, AI plays a very specific role. I don't ask it to do the thinking for me. I ask it to help organize that thinking. But let me get concrete about what this actually looks like, because the abstraction isn't helpful.

Here's a real example from my book: I had a chapter about how people avoid difficult conversations by defaulting to pleasantries. I knew the insight was there, but the structure felt scattered. I fed the draft to Anthropic’s large language model (LLM) Claude and asked: "What's the strongest version of this argument? What am I not seeing?" It came back with a framework that reorganized my examples around three types of conversational avoidance. The insight was mine; I'd lived it, observed it, thought about it for years. But AI helped me see the architecture more clearly.

Another example: I was struggling with a transition between two sections about workplace dynamics. I knew they connected, but couldn't articulate how. Claude suggested they were both examples of "emotional labor disguised as intellectual work." That phrase unlocked the connection I'd been feeling but couldn't name.

The frameworks, insights, and conclusions are mine. But AI helps stress test their coherence, varnish the phrasing, find blind spots, and sometimes surface better ways to articulate what I already believe.

My book Dwelling in a Place of Yes, a project I consider both deeply original and psychologically rich, was AI-assisted. So was my think piece Peak “Ideas Person”. Both relied on a foundation of human insight. But AI helped me sharpen, structure, and accelerate the delivery. It was less like outsourcing creativity, more like collaborating with a silent partner who doesn't require sleep and has read literally everything ever written.

But here's what I'm less comfortable admitting: Sometimes the AI suggests something better than what I came up with. A sharper metaphor. A cleaner logical structure. A more elegant turn of phrase. In those moments, there's a small ego death, the recognition that my first instinct wasn't actually the best one. It's humbling in a way that feels different from human collaboration, where you can at least tell yourself you might have thought of it eventually.

That's why, if I'm being honest, it sometimes feels strange to say I wrote a book. I did, but I didn't do it alone. Without this technology, it likely wouldn't exist, certainly not in the shape or timeframe it does. That doesn't diminish the originality of the ideas. But it does complicate the mythology of solo authorship.

We don't really have the right words yet for this kind of creative process. It's not ghostwriting. It's not automation. It's something closer to augmentation: the amplification of human intent by synthetic support. I still had to think, question, and refine. I still had to want to say something real. But AI helped me say it more clearly, and faster, than I ever could alone.

The boundaries get blurry

Let me test the edges of this framework with some uncomfortable scenarios:

Scenario 1: I'm writing about leadership and mention to the LLM I’m working with that I'm stuck. It suggests exploring the concept of "leadership as emotional archaeology," helping teams dig up buried assumptions. I love the metaphor, develop it extensively, and it becomes a central theme. Whose idea was it?

Scenario 2: I feed the LLM a rough client presentation and ask for feedback. It identifies three logical gaps I missed and suggests reorganizing the entire flow. The client loves the final version and asks how I came up with such a clear structure. What do I say?

Scenario 3: I'm debugging a creative brief and the LLM points out that my "innovative" campaign concept is actually very similar to work Nike did two years ago. I pivot based on this feedback. Did AI save me from plagiarism or prevent me from independent discovery?

These aren't hypotheticals. They're the daily reality of AI-assisted creative work. And they reveal how quickly the boundaries between human and machine contribution blur.

Creative identity in flux

There's a deeper shift happening, one that goes beyond tools and outputs. The very identity of the artist or thinker is evolving. If AI becomes a standard part of the process, does it reshape what it means to be a "creative"?

Maybe originality no longer means starting from scratch. Maybe it means knowing how to collaborate: with people and with machines. To bring taste, judgment, and vision to a process that now includes synthetic intelligence. It's not the death of authorship. It's its next form.

Think about sampling in hip hop. When this technique emerged, critics said it wasn't real music, just recycled loops from funk and soul. But of course, the artistry wasn't in the raw material. It was in the selection, the juxtaposition, the recombination.

But let me push back against my own analogy here. Hip-hop sampling was eventually accepted because the human creative agency remained obvious: the DJ's selections, the rapper's flow, the producer's vision. With AI, the agency is more distributed and less visible. When an LLM suggests a better structure for my argument, where exactly does my creative contribution begin and end?

The sampling comparison also misses something crucial about scale and accessibility. Sampling required specialized knowledge, expensive equipment, and musical intuition. AI assistance is becoming cheap, ubiquitous, and easy to use. The barriers to entry are collapsing, which might mean the democratization of creativity. Or the commoditization of it.

What makes something original isn't the source material, it's the rupture. The idea that breaks the pattern, the move that shifts the logic. AI can help sharpen those ideas, but it can't make them.

Or can it? I want to believe this, but I'm not entirely sure. What happens when AI gets sophisticated enough—and rest assured, it will—to suggest pattern breaks I never would have seen? When it starts making creative leaps that feel genuinely surprising? The technology is evolving faster than our frameworks for understanding it.

AI-assisted creativity works the same way. If your judgment is what's driving the output, if your voice is unmistakable in the end result, then the work is no less yours.

I still stand by the ideas in my work. But I also recognize that I didn't build them alone. I surfaced the thinking. AI helped me shape it. That's not a dilution; it's a deepening. The work couldn't exist without me. But it also wouldn't exist as it does without AI.

What does it mean to say "I made this" in 2025?

This is the question creative professionals everywhere are now quietly confronting. Not because authorship is vanishing, but because it's expanding. The boundaries of creative ownership are no longer defined by total isolation, but by vision and intent.

But let's be honest about what we're really asking: In a world where anyone can produce polished, professional-quality creative work with AI assistance, what happens to professional creative work itself? If the barrier to entry keeps dropping, do we get more creativity or more noise? More authentic voices or more sophisticated mimicry?

I don't think we know yet. And I'm not sure the hip-hop analogy holds when everyone has access to the best sampling equipment ever designed.

So can you be a serious artist and still use AI in your process? I think the answer is yes, if the ideas are yours. If the insights are earned. If the final output couldn't exist without your vision, your synthesis, your judgment.

But I also think we need better ways to talk about degrees of assistance, clearer standards for attribution, and more honest conversations about what happens to human creativity when machines become this good at augmenting it.

AI is a tool. A very powerful one. But it can't confer originality (for now). Only you can do that. If the work wouldn't exist without you—your intent, your taste, your perspective—then it's yours. It doesn't matter if AI helped you iterate.

Or maybe it does matter, just not in the way we think. Maybe what matters isn't whether we use AI, but how consciously we use it. How intentionally we preserve the spaces where only human insight can go.

That's not a compromise. That's creative integrity in the era of intelligent tools. But it's also an ongoing negotiation—with the technology, with our industry, and with ourselves—about what human creativity means when machines can think alongside us.

The question isn't whether this is the future of creative work, because it’s already here. The question is what we do with it.