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'Artificial intelligence' is just a snazzier name for 'applied statistics'.

The goal isn't to create thinking robots, the goal is to extend statistical methods to the realm of unstructured dumps of big data.

We don't know what "thinking robots" might be and what they're good for, but we've known about the power of statistics for a century now.

Selling statistics + big data to businesses is a no-brainer.

This is basically my observation too. That it seems hard to distinguish it from "smart & fancy algoritms". The marketing and hype around it do however imply that it's much more a path to intelligence proper, hence the question above.

The truth is that many ML researchers do care about what "intelligence" (better to say cognition) actually is, but all the funding basically comes from applied statistics problems on business data.

Nobody cares about what intelligence actually is just as long as they can package it up and sell it for billions of trillions of dollars to the business and consumer markets.

Ornithologists vs. aeronautical engineers... :)