For many products and businesses, it's not really necessary to avoid long-term dead-ends (say 3-5 years) if you can be much more effective in the short-term (say 3-12 months). So a high up-front cost (required knowledge and planning / research experience) approach often loses out to simply banging out more code, which requires little CS knowledge.

Computer Science is broad (even AI is different), but I'd say it's more about Turing's academic papers, and computational mathematics. Programming, and computers, aren't even needed, they're just models which either can or cannot derive solutions, or in a reasonable time. Such as the halting problem, P, NP, NP-complete.

In a way it's mathematical logic, but with more rigorous proofs.

Everybody else can learn a generic language with some external libraries and make almost anything they want. But that's not more academic than it is to do woodworking, or sewing. Comp Sci is academic, and one of the more important ones because it determines a lot of research other disciplines do. I.e physicists and mathematicians do comp sci, while the softer sciences run models without understanding why they work.