Well, I'm assuming of course that you can find many mistakes much faster with "robot testing", so it'd be cheaper. Of course you wouldn't find "semantic" mistakes.
This kind of testing isn't about that kind quantative, QA type testing; it's about qualitative feedback, for example:
- "We have these wireframes of this new major feature, let's get a group of people from our target demographics in a room and have them react to it and give us early feedback"
- "We think we have an idea for a new product for managing widgets, so we want to talk to professional widget managers about how they currently manage their widgets; and test our hypothesis that this is a better way of doing it"
As the previous poster pointed out, this is something that isn't easily or readily generalisable into AI.