[sacado2]

This is a recent shift lead by the ML trend. Traditionally (like 5 years ago), ML and AI were two different things, AI being the term for symbol manipulation. Expert systems, inference engines, constraint programming, SAT solving for instance. These domains are typical CS stuff: inference, complexity classes, low-level representation of data, etc. You don't need that much knowledge in math/statistics to be proficient in those fields, but you rather know what the halting problem is.

I'm working in the symbolic AI field, and sometimes use ML techniques. They are complementary. To me, ML is about induction, AI is abut deduction. They don't solve the same kinds of problems and they tend to work pretty well together.