The honest position is that AI is excellent at production and poor at judgement.
It is very good at generating layout variants, filling realistic content into a design, producing responsive breakpoints, writing component documentation, and converting an agreed design into buildable front-end code. All of that is real work that used to consume most of a design budget, and removing it is why our timelines are shorter than a traditional studio.
It is weak at deciding what the interface should do. It does not know that your customers are tradespeople checking a quote on a phone at a job site, that your highest-value users abandon at the payment step, or that your support team fields the same question forty times a week because one label is ambiguous. That understanding comes from research, and research is the part of the process we protect rather than compress.
The failure mode we see most often in AI-generated interfaces is that they look sophisticated and perform badly. Beautiful gradients, poor information hierarchy. Twelve navigation items because nobody decided what matters. A checkout that generates cleanly and loses people at step three. Every one of those is a decision problem, not a rendering problem.
So the split we run is deliberate: AI does the volume, senior designers do the direction, and every screen is reviewed against the task it is supposed to support before it moves into build.