Expert systems are basically decision trees which are "gofai" (good old fashioned ai) as opposed to deep learning. I've never really seen a good definition for what counts as "gofai" (is all statistical learning/regression gofai? What about regression done via gradient descent?). There's some talk in [1]
Yes: you fit a decision tree to your dataset in an automated fashion, that fits the definition of machine learning. Just as you would use backpropagation to fit a neural network to your data.
Oh, if the tree is made by the computer based on training data, that feels to me like what most people would agree is “artificial intelligence” in 2026 (which is why I think people should actually say “machine learning”).
That is how decision trees are usually made in my experience. Though I guess you could make one by hand. You could also make a (small) neural network by hand.
In which case you could argue that neither DTs nor NNs are ML. Only the training itself is ML/AI. An interesting perspective, but this will probably just confuse the discussion even further.
[1] https://www.beren.io/2023-04-10-Why-GOFAI-failed/