In my classes, I tell students that "AI" is the general population term for machine learning, data science, and "traditional" AI (pathfinding, planning, logic p

In my classes, I tell students that "AI" is the general population term for machine learning, data science, and "traditional" AI (pathfinding, planning, logic proofs, etc). They all touch on a part of AI, but the differences are hard to explain to non-tech people. People will interchange ML with AI and still mean the umbrella "all of it" concept. That's one of the reasons the article talks about getting more concrete tools that are used in the workflow. Laypeople might think a switch statement is AI and their potential customers also think its AI, that doesn't mean its really AI. I'm actually booked to give an AI talk for business managers later this month and this is something I'm planning to cover. The article does a good job at outlining what to look for when you get those "AI for X" sales pitches.