You're right that adoption is very slow. I'm convinced that businesses could save trillions of dollars by applying existing weak AI to their problems. Why aren't they doing it ? For one thing there's a huge gulf between the average business person's understanding of what is possible and what actually is. On the other hand the people who understand the technology don't have domain experience in various businesses. You can't develop solutions if you don't know what the problems are and it's very hard to guess at what economically relevant problems exist in fields you've never worked in.
There are probably other barriers as well. Domain experts are unlikely to champion technologies that may, well, replace them. Bayesian networks were developed in academia 20 years ago that outperformed doctors at medical diagnosis. Why aren't they being applied ? There are probably many reasons but I suspect conscious or unconscious resistance on the part of the medical community plays a significant role.
As for a talent shortage, I don't buy it. I'm exactly the sort of person this article talks about, with a strong mathematical background, excellent implementation skills and real world experience in developing and applying machine learning algorithms that have made millions of dollars for my former employers. I have had a website and a LinkedIn profile for over a year that make this fairly clear. How many consulting inquiries have I had ? Exactly zero.