After the Panic
The creative industry is now entering its third year of AI pearl-clutching. Depending on the day, AI is either an overhyped autocomplete machine or the invention of fire. A toy. A weapon. A messiah. A mass layoff. So naturally, the collective response has taken the shape of grief. Denial. Anger. Bargaining. Depression. Acceptance. And a lot of long LinkedIn posts written in the tone of a hostage note.
One of the most popular refrains bubbling up through the discourse is the imperative to make work that’s “more human.”
You hear it in conference keynotes. You see it in agency positioning decks. You read it in manifestos typed with the solemnity of a war declaration. Humanity has become the rallying cry against the machines—the antidote to AI-generated slop flooding our feeds. Which raises the obvious question:
What, exactly, does “more human” mean?
Because when people say it out loud, they usually offer a nebulous grab bag of words that have been dead for years: authenticity (god, I hate that word), craft, emotion. The same qualities we’ve always claimed were table stakes for good work. Lately, though, “more human” has been operationalized into something even worse: deliberate imperfection. Rough edges. Unfinished aesthetics. The visual equivalent of showing your work.
Consumer giants adopt soft and loopy typography to signal harmless sincerity. Photographers meticulously compose lousy shots, blown out with simulated flash to convey proletariat credibility. Illustration is infantilized and performatively naive. We get faux flexography. Faux film grain. A 1970’s pastiche without a whiff of irony. It’s as if being human means being sloppy while polish and refinement are somehow inhuman.
This is a dead end.
If “human” becomes synonymous with “unfinished,” then we’re conceding that craft, excellence, and refinement belong to the machines. We’re painting ourselves into a corner where the only way to prove our humanity is to be stuck doing worse work. That’s not a philosophy. It’s cope.
The fear driving this panic is obvious: we’re approaching a moment when you won’t be able to tell whether something was made by a person or an algorithm. The outputs will be indistinguishable. We’ll have lost something essential. But let’s be honest, we’ve been making work indistinguishable from each other for years. And we didn’t need AI to do it. We were producing plenty of slop all by ourselves, thank you.
A better way of making the same mistake
Science fiction writer Theodore Sturgeon famously said, “90% of everything is crap.” The quip landed so cleanly it became a rule of thumb: Sturgeon’s Law. And it applies to branding with the cruelty of a spotlight. Spend a day actually paying attention to the branded content you encounter in your physical and digital environments (you’re going to hate me for this). Roam aisles, examine check-outs, read the tops, bottoms and sides of “enshitified” websites.
Considering this ever growing ocean of sludge crashing into our lives, it’s hard to disagree with Sturgeon. Ninety percent of everything is crap. And to be fair, we have to include what we make in this percentage. One of the consistent criticisms of AI output is that it tends toward average work. I think we’d all agree that average is an upgrade from crap, which suggests a more uncomfortable fear beneath the panic: What if AI slop is actually better than the human slop most of us have been producing?
That’s not a fear of machines. That’s a fear of the mirror.
Because long before ChatGPT wrote its first anodyne headline or Midjourney generated its first six-fingered human, the branding world was already drowning in sameness. Look at any category.
DTC brands: sans-serif wordmarks and creamy pastels.
Tech: friendly rounded type, abstract geometric logos, the same three gradients passed around like a communal vape.
Wellness: earth tones, minimalist packaging, copy wrapped in the gauzy tone of a person who has never experienced heartbreak.
Craft beer: a thousand “distinctive” labels that all somehow look like they came from the same design school, taught by the same professor, in the same week.
SaaS: landing pages so identical you could swap hero sections and no one would notice.
Fast fashion: a closed loop of derivative mediocrity moving at the speed of the shipping container.
Even the great “heritage” rebrand wave, featuring Burger King, Pizza Hut, Pepsi and half the category rediscovering their roots at exactly the same time. It felt less like a return to identity and more like a synchronized swim. Everyone is using the same playbook. Following the same best practices. Gaming the same algorithms. Optimization became the creative brief.
AI didn’t create this problem. It created a better way to make the same mistake.
The Cult of Optimization
John Wanamaker famously said, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” For over a century, that was the uncomfortable truth of marketing. You threw things into the world and hoped something stuck. There was mystery in it. Risk. A kind of creative gambling. Then came the pixels. The attribution models. The dashboards. The promise that we could finally solve Wanamaker’s problem. Google, of course, solved it and became a multi-trillion-dollar company in the process.
But in solving for efficiency, we eliminated something essential: the space for surprise. That “wasted” half wasn’t just waste. It was the half where the weird stuff lived. The half where breakthroughs happened. The half where marketers were forced to field something that hadn’t been tested, focus-grouped, researched, and optimized into submission. Super Bowl ads used to be genuine creative risks. Brands spent millions on ideas that hadn’t been pre-validated by a panel of tired suburban adults. Now everything is pre-tested. Every edge sanded down. Every punchline softened. Every risk eliminated. Because if you can measure everything, you can also justify doing nothing interesting.
We traded the messy possibility of breakthroughs for the warm certainty of mediocrity. This is what passes for innovation. Optimization didn’t just make branding more efficient. It made it less alive.
This isn’t just a branding phenomenon. In his book Blank Space: A Cultural History of the Twenty-First Century, W. David Marx argues that despite an unprecedented abundance of content, the last 25 years have seen remarkably little cultural innovation. Instead, we’ve gotten reboots, nostalgia, and formulaic trends driven by commercial and technological forces.
The result is what Marx calls a “blank space”—a cultural landscape that feels simultaneously full and empty. Lots of content, little that feels genuinely new.
Sound familiar?
We’re living in branding’s blank space. Lots of brands, little distinction. Professionally competent and utterly forgettable.
Humans. They’re the Worst.
So now AI arrives, trained on the last two decades of this optimized sameness—capable of generating infinite variations on the same themes. Of course it feels threatening. It’s not just producing slop. It’s producing our slop. Faster. Cheaper. On demand. So, we use signs of “humanity” to distinguish our work from the synthetic deluge. We’ll out-human the machines. We’ll lean into what makes us uniquely human: creativity, emotion, authentic connection.
But here’s the problem: Humans love formulas. They (we, I guess) like what they’ve already seen.
We are pattern-seeking creatures. We conserve cognitive effort. We copy what works. We follow playbooks. We optimize. We do the thing that feels safe because it reduces the risk of being wrong. The homogeneity in branding isn’t a failure of humanity. It’s humanity working exactly as designed. “More human” doesn’t solve the problem. It doubles down on the instincts that created it. And worse, it’s philosophically incoherent. Humans have been making forgettable, derivative, paint-by-numbers work for centuries. Most human-made work is bad. Most of it is forgotten. The fact that a person made something doesn’t make it valuable. It just makes it expensive.
Less “Human.” More Compelling.
The way out of branding’s blank space isn’t being “more human.” It’s being more compelling. And compellingness doesn’t come from the residue of humanity. It comes from specificity of human understanding. There’s a rock & roll design firm in Sweden called Snask. Their motto is: Make Enemies, Gain Fans.
Read that again. Make enemies. Gain fans.
This is the opposite of everything the optimization mindset has taught us. It’s a direct challenge to the idea that good branding means appealing to as many people as possible. If everyone likes it, no one loves it. Distinctiveness requires alienating some people. It requires making choices that certain people will disagree with. It requires building for a specific audience with specific motivations rather than trying to find the lowest common denominator that offends no one. This is what algorithms fundamentally cannot do.
Algorithms are trained on aggregates. They find patterns across millions of data points and identify what appeals to the most people most of the time. They reward pattern-matching. They reward familiarity. They reward the already-proven. Brands that matter aren’t built for aggregates. They’re built for specifics. They know which humans they serve. They understand what motivates those particular people—not in the vague sense of “everyone wants connection,” but in the specific sense of understanding differentiated human motivations and building brand experiences that align with them.
Some people are driven by achievement and status. That’s Peloton’s entire model: leaderboards, badges, public performance. Others are driven by tranquility and safety. Headspace isn’t selling meditation. It’s selling calm. Others are driven by idealism and moral alignment. Patagonia doesn’t just sell jackets. It sells a worldview. Others are driven by belonging. Trader Joe’s turns grocery shopping into a treasure hunt and a shared language. These aren’t preferences. They’re different ways of moving through the world. And a brand that genuinely serves one of these motivations will necessarily alienate people driven by others.
That’s not a bug. That’s the feature.
Patagonia makes enemies of people who think environmental activism is performative virtue signaling. Supreme makes enemies of people who think streetwear is shallow. Liquid Death alienates anyone who thinks water should come in a normal bottle. Oatly’s tone pisses off traditional dairy consumers. CrossFit repels as many people as it attracts.
These brands have fans because they have enemies. They’re specific. They stand for something. They make choices. And those choices create distinctiveness.
What This Means in Practice
If you want to build work that survives the AI era, you don’t need to become “more human.” You need to stop behaving like a machine. That means abandoning a few assumptions the industry has treated as gospel for the past twenty years:
Stop trying to win everyone.
The omnivore approach produces bland, forgettable work. Accept that building something distinctive means some people won’t connect with it. That’s the point.
Stop following the playbook.
If everyone in your category is using the same SaaS positioning framework, the same “We’re the Spotify of [industry]” metaphor, the same mission statement containing the words empower, authentic, community, and innovative—do something else.
Reclaim Wanamaker’s “wasted” half.
The space for distinctiveness lives in the unmeasurable. The surprising. The things that don’t test well because they haven’t been done before. Stop optimizing every decision. Leave room for risk.
Build for motivations, not demographics.
Not personas. Not vibes. Actual psychological motivations that drive behavior. Understand what moves your audience and build a brand that aligns with it—even if it alienates others.
Accept that distinctiveness is uncomfortable.
It means making choices that some people—maybe most people—will disagree with. It means having a point of view. It means potentially making enemies.
None of these principles are mind-blowing. They’re simply best practices rarely practiced.
This isn’t a call to ignore data. It’s a call to recognize that the data is leading everyone to the same place. The strategy has become a straitjacket. The optimization has become the religion. And AI is simply the latest prophet (or god, if you’re an accelerationist).
Your Time Is Limited. Stop Spending It on Forgettable Work.
Every truly creative professional I’ve ever known has a career clock ticking in their head. It counts down the number of hours left to do transformational work. And if you’re taking the AI doomer view, that clock is ticking faster every day.
So here’s the question we should be asking now:
Not “Is it good?”
Not “Will it perform?”
But: Is it worth it?
Is it worth the time, money, and career effort we’re putting into it? Because if the work just adds to the noise—if it’s interchangeable with what every other brand in the category is doing—then no. It isn’t worth it. If the work is optimized for efficiency but devoid of distinctiveness—if it checks the boxes but doesn’t actually connect with anyone—then no. It isn’t worth it. The work is worth it when it breaks the cycle of homogeneity. When it serves specific human needs for specific people. When it takes a risk on being distinctive rather than playing it safe with sameness. Not by being “more human.” But by being more precise about what actually motivates particular humans.
The irony of the AI panic is that it’s made us focus on the wrong threat. The danger isn’t that machines will replace human creativity. The danger is that we’ve been operating like machines for years. We’ve been following formulas, optimizing for aggregates, producing work that is technically proficient and spiritually empty.
AI didn’t create branding’s blank space. We did. By choosing efficiency over distinctiveness. By choosing reach over resonance. By choosing to play it safe rather than make enemies. The solution isn’t to be more human. It’s to be more specific. More distinctive.
Serve someone.
Not everyone.
Make enemies.
Gain fans.
That’s how you fill the blank space.
