Ask five different AI image generators for a modern minimalist logo for a tech startup and look at what comes back. A circle or a rounded square. A gradient, probably blue to purple. A little abstract mark that could plausibly represent an arrow, a leaf, or a lightning bolt, nobody is quite sure which. Run the same prompt a hundred times and you get a hundred variations on the same four or five ideas, because the model is not inventing, it is averaging across everything labeled modern minimalist logo in its training data, and the average of a category is, by definition, the least distinctive thing in it.
The blanding problem was already here
Generative AI did not invent brand sameness. Look at the last decade of sans-serif wordmark rebrands that all landed on some version of the same rounded geometric typeface, and you will see human designers converging on a trend well before any model touched a prompt box. What AI does is remove the friction that used to slow that convergence down. A trend used to spread through agencies and conferences over a few years. Now it spreads through a shared training set instantly, at the scale of every small business that types a prompt instead of hiring a designer.
Where it could actually help
- Fast, cheap exploration of genuinely odd directions a human might not bother sketching, if someone pushes the prompt past the obvious answer
- Rapid iteration on execution details, spacing, weight, color, once a distinctive concept already exists
- Lowering the cost of testing a mark against real constraints, small size, one color, motion, before committing
None of that happens by default. It happens only when a human treats the output as a rough draft to argue with, not a finished answer to accept. The studios and founders getting real value from these tools are the ones generating fifty options and rejecting forty-eight of them for being exactly what everyone else is generating, not the ones shipping the first result.
A tool trained on the average logo will hand you the average logo, unless someone in the loop insists on something else.
The real variable is not the tool
Whether generative AI makes blanding worse or better depends entirely on who is holding it and what they are willing to reject. In the hands of someone chasing speed, it accelerates sameness. In the hands of someone chasing distinctiveness, it is just a faster sketchbook, and the discipline still has to come from the human.