Noodling on a theory I had at the start of the AI wave:
Aside from translation & image gen, AI software solutions are almost universally solving problems where a structured data model would solve the problem better.
Of course, it takes significant thought to model these problems as data. This isn't a claim that all AI problems should be solved by data modelling, but when we are building AI systems we should be cogniscent of which deterministic problems we're approximating in stochastic space.