The only metric that matters for a business is whatever helps their bottom line. No one really cares about competitive results if they can just fine tune some open source model on their own data set and get good business outcomes. So if there is good data and access to compute infrastructure to train and fine tune some open source model then the only obstruction to figuring out if AI works for the business or not is just a matter of setting up the training and deployment pipeline. That requires some expertise but that can be learned on the job as well or from any number of freely available tutorials.

I don't think AI is hard to learn. The fundamentals are extremely simple and a competent software engineer can learn all the required concepts in a few months. It's easier if you already have a background in mathematics but not required. If you can write software then you can learn how to write differentiable tensor programs with any of the AI frameworks.