The sameness problem: why AI content stops selling once everyone has it

TechCrunch described a problem familiar to anyone scrolling food delivery: AI-generated dish photos and menu descriptions across different venues are indistinguishable — the same gloss, the same light, the same adjectives. At first such content lifted conversion; now it breeds distrust: the customer realizes they're looking at a neural network, not a cutlet.

It's the pattern of any mass-creativity technology: while few have the tool, it confers advantage; once everyone does, it moves the bar and devalues itself. The win shifts to those who combine: AI for speed and volume, authenticity for trust.

A practical recipe for business in Kazakhstan: split content into layers. Technical descriptions, answers to standard questions, reminder posts — AI's territory, that's hygiene. But in the shop window — real photos of your product, genuine reviews, the team's faces: what a competitor cannot generate in a minute. Paradoxically, the more generated content there is around, the more the real thing is worth.