ArticleIssue #165 | Adequacy Is Free. Which Makes It Worthless.
Last week, I wrote about creative being math wearing a costume – that the ad itself is just the visible shadow of the work that actually matters. This week I want to zoom out one level. The dynamic playing out in creative is playing out across every market AI has touched, and most marketers/brands/operators are reading it backward.
Scott Galloway has an observation I keep returning to: the sexier the space, the better you have to be just to survive. Sexy markets attract more entrants. More entrants compress margins. Compression raises the bar for everyone left. Restaurants, fashion, media, sports, content – all share a failure curve that isn’t really about the product/service. It’s about the population of people willing to take the swing.
For most of the last century, that dynamic stayed in its lane. Software, professional services, B2B tech, consulting – none of those were sexy. They were grindy. Grindy markets had a built-in tax on entry: fewer competitors, higher operational floor, more room for competent operators to build real businesses without needing to be exceptional.
AI broke that.
Not by making grindy markets sexy. That framing gets the mechanism wrong, and most of the LinkedIn commentary celebrating the “democratization of expertise” is built on it. What AI actually did was collapse the cost of appearing competent in writing, design, analysis, content, code & strategy to something approaching zero. Competence alone used to be a moat in those markets – quiet, but real. That moat is shrinking, and what’s left is no longer sufficient.
AI Didn’t Make Everyone Great. It Made Everyone Adequate.
The prevailing narrative is that AI enables everyone to produce great work. That’s wrong on its face. AI did not raise the ceiling. It raised the floor on what mediocre looks like.
The chasm between looks competent and is competent gets wider with every passing week and every new variant of a foundational model published. The reality is that AI is exceptional at the first and incapable of the second. It produces work that passes a quick skim and collapses when interrogated by a competent expert.
You can watch this play out. Brands with generic positioning and unremarkable perspectives are losing their share of visibility in AI-generated summaries, AI search, and AI-driven discovery. The systems running deduplication have gotten very good at recognizing that 10,000 pieces of content saying the same forgettable thing should collapse into one citation…which means 9,999 of them won’t be cited.
Now extend that logic. When everyone has the same tools and the same floor, survival doesn’t come from being generically better. It comes from being specifically, memorably different – different in a way an audience recognizes and remembers.
Most brands resist this (especially those in growth mode) because specificity feels like shrinking the addressable market. It feels like leaving money on the table. It feels like picking a smaller pond when the whole point was to fish the ocean.
That instinct is mathematically wrong.
The Specificity Math
Last year, Rand Fishkin (he of SparkToro fame) shared research assembled by SparkToro and Datos that indicated progressively more of the “middle of the funnel” (assessment, evaluation, solution-fit, etc.) was happening out of public view, in private Slack groups, WhatsApp chats, text chains, discussion boards, in-person events, etc. I mention that now for two reasons: first, our data shows the same thing, and second, if that’s true (and I think it is), then the only way to win those customers is for your content/perspective to be share-able.
A clear perspective is forwardable, which drives word-of-mouth. The audience you actually reach is the audience the offer was built for, which increases conversion rates + qualification rates. There’s no substitute for a perspective nobody else holds, which drives pricing power. A newsletter that reaches 1,500 readers with a 75%+ open rate and 10% forward rate beats a list of 150,000 with a 10% open rate and a 1% click rate. It isn’t even particularly close.
The broad play is a war of attrition against everyone else who had your idea. You compete on volume, price & pain tolerance. The specific play is a different game entirely – it’s a monopoly of one. You are the only place that the audience can get that perspective. That isn’t a smaller market. It’s a defensible one.
Watch what’s happening in financial media. Every bank, brokerage & fintech now publishes AI-generated market commentary. The output is mediocre – every one has the same facts, the same “context” and (laughably) the same quotes. Every one of them is functionally invisible – opened by nobody, forwarded by nobody, quoted by nobody. You could delete 90% of those newsletters from the internet and I doubt a single soul would notice. Meanwhile, a handful of independent analysts with sharp perspectives and narrow focus areas have built paid audiences willing to pay real money for the privilege of reading them. The generalists are drowning in their own adequacy. The specialists are building niche media empires worth millions.
The same mechanism applies anywhere attention is mediated by content – agency positioning, B2B SaaS, creator economies, legal and health verticals. (It applies less in markets where the moat is switching costs, regulatory complexity, systems integration, or procurement-driven trust networks. If you’re selling enterprise IT with a 2-year sales cycle, this issue is about your marketing, not your moat.)
AI accelerates the divergence in both directions. It floods the ecosystem with more of the same get-it-anywhere drivel, which makes the can-only-get-it-here content stand out like the girl in the red dress (yes, that’s a Matrix reference). The noise makes the signal louder. A brand with a genuinely differentiated perspective can use AI to accelerate distribution, refine their execution & amplify their pre-existing point of view. That’s the tool used correctly – applied to thinking that already exists and serving as leverage on whatever edge the user/brand brought to the table.
Most brands get it backward. They use AI to replace the thinking instead of accelerating it. When you do that, the output is hollow – indistinguishable from 1,000s of other pieces regurgitating the same uninteresting ideas. Those brands mistake the artifact (the newsletter or LinkedIn post) for the work (the perspective/world view/philosophy that gave rise to it). And, in the end, all AI does is increase the volume, lower the resonance and pump more generic, unmemorable, unremarkable content onto the internet.
This is the artifact-outcome problem on cocaine. The deliverable – the newsletter, the downloadable, the PPT, the article, the ad – looks real. It passes a quick skim or a cursory inspection. But the deliverable was never the value driver. It was the visible artifact of a deeper mechanism – a perspective, a relationship, an insight, a trust network – that actually produced the outcome. AI replicates the artifact and leaves the mechanism untouched. That is why the vast majority of AI-generated work technically exists but functionally accomplishes nothing.
If your content, creative and positioning are indistinguishable from your competitors’ in a blind test, you don’t have a brand. You have a participation trophy in an increasingly crowded auction. Volume on top of sameness is an expensive way to pay more for the same invisibility. And the move most teams resist – deliberately narrowing the addressable market – is usually the highest-leverage move available. It sounds crazy – until you realize that a defensible position in a narrower market has an exponentially greater expected value than an undefended position in a broader market.
Generic is a death sentence now. It just happens to be a well-written one.
Cheers,
Sam
