There always has been a stunning amount of inertia from the old big data/ML/"AI" guard towards actually deploying anything more sophisticated than linear regression.
There's a lot of areas where you need to be able to explain the decisions that your AI models make and that's extremely hard to do unless you're using linear regression. E.g. you're a bank and your AI model for some reason appears to be accepting applications from white people and rejecting applications from african americans or latinos. How are you going to show in court that your model isn't discriminating based on race or some proxy for race?