Ask an AI model for a website layout and you will get something plausible within seconds. Ask for ten and you will get ten that look strangely alike. That sameness sits at the heart of a debate: models can make things, but can they make things with taste? Some startups now focus on AI design taste, collecting human preferences about visuals and feeding them back into models. Whatever you think of those efforts, the underlying problem is real, and it touches anyone who uses AI to produce visuals.
What taste means in practice
Taste sounds vague, but in design it breaks into concrete choices. Spacing between elements. A limited, consistent color palette. Type that suits the tone of the content. Hierarchy, meaning the eye knows where to look first. And restraint, meaning the designer chose to leave things out.
A person with taste is mostly someone who has seen many examples and developed a feel for what works and why. They can often say what is wrong with a layout even when they cannot fix it. That ability to critique is exactly what is hard to capture in AI design taste.
Why AI output drifts toward the average
Models learn from large amounts of existing material. When you give a broad request, the most likely answer is the most common one. The result tends to be competent and forgettable: a centered headline, three feature boxes, a soft gradient, a stock-style illustration.
There is also the training signal. Many systems are tuned using human ratings, and people often prefer outputs that look polished and familiar at a glance. That can favor safe choices over interesting ones. A model rewarded for being liked by most people will rarely take a risk that only some will love.
None of this means AI cannot produce good design. It means the default will not be distinctive, and you have to do some work to move it. In that sense AI design taste is less a property of the model than a product of the person steering it.
Five quick tests for AI design taste
Judging AI design taste does not require a design degree. Try these checks on any generated slide, poster or web page. First, the squint test: blur your eyes and see if you can still tell what matters most. Second, the removal test: delete one element at a time, and if nothing is lost, it did not need to be there.
Third, the swap test: replace the brand name with a competitor’s, and if the design still fits perfectly, it is generic. Fourth, the reading test: is the text legible at the size and contrast used, including for people with weaker eyesight? Fifth, the detail test: look for artifacts such as warped letters, misaligned edges, or hands and objects that do not quite make sense.
Run the tests on your own work first so you know what a pass looks like. A pass should feel boringly obvious: the page says one thing, clearly, and nothing else competes with it. That is the standard against which any AI design taste claim should be judged. Many people find that their first, favorite draft fails the removal test badly.
These checks work for human designs too, which is the point. Good AI design taste in a tool should show up as passing them without your help.
Steering a model toward better results
Prompts shape AI design taste more than people expect, so spend your effort there. Give constraints, not adjectives. “Modern and clean” produces the average of every modern clean page. “Two colors, one serif headline font, a lot of empty space, no icons” produces something specific. Name the audience and the job of the page, such as helping a nervous first-time buyer feel safe.
Bring references. Show examples you admire and say what you like about each: the spacing, the weight of the type, the way photos are cropped. Models respond better to concrete material than to mood words.
Iterate in small steps. Fix one thing at a time instead of asking for a total redo, or you will lose the parts that worked. Keep your own version history so you can return to an earlier draft.
Finally, keep a human in charge of the final call. Brand identity is a cumulative thing, and details like a logo carry years of meaning, as our piece on what makes a startup logo work explains. A model can offer options, but someone has to decide which one feels like the company.
The same caution applies to other generated media, such as AI short-form video tools, where speed tempts people to accept the first result.
It may be that models eventually get better at reflecting a particular point of view, especially if they are trained on curated examples from a single designer or brand. Until then, treat AI design taste as something you supply. The model is fast, the judgment is yours. For background on the discipline itself, see the Wikipedia article on design.
