Main problem is not language, but that AI models still not creators but imitators (I mean only deep AI, like LLM, will explain).
Yet I read about very simple test - just ask AI to draw glass of wine - it could draw only half-filled glass if trained on half-filled glass and could not grow to higher abstraction, abstract glass from fullness.
I don't know, what we really need to overcome this limitation, but while it exist it will limit all AI usage.
To be more constructive, I think, most practical languages for AI could be something like SQL, mean fully declarative, without any imperative part, so AI will just translate human text to language.
So may be solution, some hybrid approach, where human define limits on solution; deep AI is just translator; and some classic optimization technique will generate solution (on HN appeared link on query compiler book, where you could see huge list in contents, and later I'll check, before I seen link with list of just all existing optimization approaches).
Other possible solution I see, may be some hybrid of deep AI and semantic AI. For semantic AI exists problem that it need to define any possible way, it cannot even hallucinate to create something new.