TL;DR: If you're the scale of a Fortune 20, you're not gonna use these tools unless it's a hosting platform or just a start. If you're the scale of a Fortune 100, they are a great start that you can tweak and you will likely use them. If you're the scale of a Fortune 1000, then these are great tools to add to your arsenal until you decide that you want to focus on getting good data scientists. If you're smaller than that you might not be able to afford these tools.
Longer explanation: DataRobot is probably the second best autoML solution out there (I'm biased, I realize).
AutoML tools are amazing at going from the 'we want something' to 'we have something' level of specificity and completeness. They do a bunch of (basic, thoughtless) feature engineering and then try a bunch of (basic, thoughtless) parameter tuning to get to the best result you ask for. Huge caveat - you still need to understand what to ask for and how to interpret the result(s).
So if you're at a firm without much in the way of capacity it can scale your capability really, really well. As long what you want is basic, thoughtless models. And then these tools let you host a model so you can score against it.
Don't take that as a necessarily bad thing. Most firms don't have this level of capability and so if what you lack is someone who can write the code then these tools can be amazing at scaling your capabilities. And if you're coming from nothing or a 10% solution then this will get you to an 80% solution and do so quickly.
Now...that being said...if you want it to work better you can't stop with just DataRobot (or any of the other autoML tools). You're not gonna get great. You'll just get good enough.
For what it's worth, I think there is going to be a niche of implementation folks that use tools like DataRobot to get orgs from nearly zero analytics to basic ML level for the next 2 - 10 years.