But the freshly graduated PhD does not, and is usually the person in charge of making the decision of whether to use the software initially when the field is new. Which would be a case of protecting their own job at the detriment of the company
I've personally not seen this happen. Instead, I've seen many oversold ML/AI tools that offer no advantages over using open and freely available tooling that the data scientist (with or without PhD) is already familiar with. I know this must be frustrating to ML solution vendors, but as with any product, the value proposition has to be there and easy to see for the domain expert. And the value has to be great because the downside is the vendor lock-in of the proprietary solution. Hence, ask yourself: given a green field real world ML project, would you use your tool (with the the same learning algorithms, data manipulation methods etc. under the surface as everybody else), or resort to using some battle proven free and open stack.
