Everything you outlined is a use case that is powered by machine learning algorithms. You can discuss all of them without using the phrase "AI." They all likely started with rules engines that solved a real business problem and iterated over time to use more sophisticated back ends.
The thing that I don't appreciate in this field is that companies seem more focused on discussing their "AI" than the actual problems they hope to solve. When I see this, my mind jumps to the assumption that these companies are either: 1) looking for easy valuation multiples. 2) looking for a way to impress VCs/investors. 3) they don't actually understand the problem they are solving. This is admittedly a big stereotype on my part, but this stereotype was built on pattern recognition over time.