It's always been AI. Pretty much any decision-making toolset can be classified as artificial intelligence.

Unless, of course, you subscribe to the "AI technique is no longer AI when it becomes real" school of thought

Last year, our Image Recognition pipeline was partially built (cleaning, clustering, invariance - essentially ready to feed into 'AI') when we had to stall that part of the project, whack a classifier in front, and pivot to tackling some unexpected problems elsewhere. As such we weren't comfortable calling it Image Recognition, so called it Image Analysis or 'IA'. I loved the fact that IA was AI backwards, almost "It isn't AI, it is IA!".

Now I am waiting to use the sentence "Our IA pipeline makes use of several types of AI" without contriving the situation for it. Its the little things that keep you slightly insane.

Why is this a problem? I'm pretty sure that's been a typical approach in the field since the 80s or before.