"AI" == "what (through tech) can replace a professional"

It may seem similarly vague, but it does in fact open interesting, productive, and necessary questions. A "computer" was a professional crunching numbers - "replaced", "easily" because of the deterministic procedural nature of said work, but what about the technical effort to arrive there, and what about the less "mechanical" jobs? When do "processes" become "intelligence"?

Some of us had studied AI originally to study the mind - "how do we formalize thought". It's the interdisciplinary, transversal nature of the area.

Also maybe compare that with that large and important intersection between CS and Economics - the "science of optimization" and its implementation in efficient IT systems. The effort in terms of that different discipline may not be evident, yet lots of engineering is "optimizing" and the generalization of those solutions we call Economics (see the book Algorithms to live by).

So: the term "Artificial Intelligence" may not be important as CS solutions to practical problems are built (you just focus on the better solution), but there is relevance to the "side disciplince" of AI, and from that perspective that is the cone, the scope anyway. "How would an intelligent solver approach the problem".

I disagree. AI is doing exactly what it was predicted it would in science fiction.

The computer can now literally talk to you in natural language and then perfectly produce sophisticated actions in response to completely arbitrary and unstructured input. It trivially passes the Turing test. By any definition prior to the year 2023 we are living with Artificial General Intelligence and it’s here now.

Game AI uses behaviour trees, usually coded by hand. Decision trees are used for classification and are normally learned from data. The latter are a traditional AI technique from the early days of the modern machine learning era, in the 1990's.