We did a DARPA-funded project using AI in design. In that case, the data that the AI learned from was generated by models. To kickstart it we first set the inputs over a broad range and let the model run and generate results, then trained the AI on the input/output pairs that represented “good” results.
Then we let the AI take over on setting the inputs, looking at the outputs, and training itself on the good results. The AI eventually learned to generate good designs that no one had thought of. That was eye-opening. AI demonstrated an ability to tease out relationships from these complex highly coupled models that our meatware did not see.