It's absolutely data mining, but it's far from worthless.
Every time you go to Amazon and it recommends something to you, guess what, that's data mining using basically the same techniques that this service will use. And as you might expect, that equates to big $$$ for them (or else they wouldn't be bothering).
Many many fields use the technology, particularly the medical fields for analyzing the relationships between a large number of input variables (which may or may not be correlated) and some desired output variable. Spam filters, Google Search itself... all data mining algorithms. Nah, no money to be made there...
Now, the reality isn't as simple as 'upload the data, training the model, and generate predictions' normally. It takes time to figure out what factors to include, ETL'ing the training data from the actual source(s), plugging in algorithm parameters, and carefully validating your output model. Most models I've worked have taken several iterations to get right as you learn more about your input data relationships as you use the model.
And your second sentence is sadly true, if management wants a certain output, then the endeavor is pointless. But when used appropriately (and it's on the experts to explain the limitations of the tech to the users), this stuff is really powerful.
But will a lot of businesses be willing to send their 10 year history of accepted/declined credit card transactions with all the related demographic data to the cloud? Or their medical scenarios with the medical details of each patient? I think not. The type of data most mining projects use is critically sensitive. So I predict this will be limited to experimental users 'playing around', nothing more.