AI and ML have different goals, which sometimes overlap. The goal of ML is to discover relationships in data that can only be (easily) observed by a machine. That usually serves as decision support data for a human decision maker or another more conventional algorithm. This is usually based on an entire data set at once. Accuracy and precision are valued over quickness and robustness.

AI is about substituting human decision makers or other conventional computer decision algorithms. AI is used for situational decision making. It needs to be quick (like the conventional algorithms) while also recognizing the nuance and multi-dimemaional nature of a lot of decisions. Robustness and quickness are often valued more than precision.

IOW the GP is only using ML for everything because it is a buzzword.