First problem: it is so hard to define “what is right”
A math problem is solved. A piece of software does what it is supposed to do. The travel itenary takes less than 14 days. These are all goals that can be easily be verified, including by AI. This means that it is possible to train AI models to reach these goals, and/or teach an AI agent to check the result against the spec.
Design is harder. The functional elements are easy to check. Does the page contain the information it is supposed to? But layout?
There is the overall impression. Most (but not all) humans can see in an instant whether design looks good or poor. But it is hard to verbalize what makes it that way. Colors, hierarchies, proportions, alignments, white space.
A trained human designer can iterate towards a results that “looks better” by making lots and lots of small tweaks. Trying some of them, rolling back, trying something different.
Second problem: a visual rather than a text-based feedback loop
A picture says more than a 1000 words, and that is a real problem for a technology that is trained on predicting what is the most likely character of text that should come after the 3 million previous ones. Take a screenshot. Analyze the picture. Milliseconds for a human, not so for an AI model.
Eventually, this will be solved as well. Until then, we need some shortcuts.