Expert systems did catch on and do see widespread use - they're just not called AI anymore. It's 'business logic' or 'rules engine' now. The issue with SVMs is

Expert systems did catch on and do see widespread use - they're just not called AI anymore. It's 'business logic' or 'rules engine' now. The issue with SVMs is that they get intractably expensive for large datasets. The cost of training a neural network scales linearly with dataset size, while the kernel trick for SVMs scales with dataset size squared. You could never create an LLM-sized SVM.