Agree 100% - the single largest problem with applying ML to anything is getting (1) enough (2) accurate (3) representative (4) correctly labeled data to train and validate the models.

Everything else is noise. For any proposed ML project, the first question you should ask is "Where are you going to get the training data?"

If someone tells you "Oh, getting data will be the easy part", back away very slowly :)