A lot of AI hype reminds me of the hype of data warehouses. The amazing predictions you were going to get. Turns out getting the data and/or using 'AI' is easier than asking the right questions and figuring out what to do when you get a particular result. Both of these tools are good at what they do. But the predictions of what they can do seem a bit off the mark. Even the failure modes seem to be mirroring a lot of what happened with data warehouses 'your data is not right' 'your data is in the wrong form' 'your filters were not right' 'you used the wrong topology' and so on.

Not saying anything bad here it is just an interesting observation of 'history repeating'.