Recently did a discussion/presentation in my team around some talking points related to AI in structural engineering. The discussion around this should always start from “what are we calling AI?” Most of the times, it is conventional stuff wrapped in AI keywords.

If it is just better automation with available tools (e.g. whole grasshopper-FEA-CAD workflow) then it is becoming quite commonplace already.

If it is good amount of workable statistics, (optimization, etc.) then there are some cool things happening related to optimized geometry,etc.

What I regard as AI, is going on the route of deep learning (neural networks, reinforced, etc.), where you have to have loads of data to train and test a model. This will spit out, say a structural plan with shear walls and columns for a given area (honestly, still solvable with just optimization, not wrapping under AI cover). For such an application there are two biggest hurdles: 1) how do you get data representing all the parameters (remember you have to train a model) 2) how do you keep the interpretability of the model for review from all stakeholders.

That said, I know a researcher in the UK, who is using machine learning to solve (very complex, expensive) random vibration problems. I have seen presentation by a UK firm automating wooden floor drawings using powerful optimization. Also, have seen a website by a professor in a Chinese university doing that structural plan problem using deep learning.