I wish I could upvote this twice. This is the exact problem preventing widespread adoption of "AI" throughout most businesses. A model that is 99% accurate is not good enough for most mundane business tasks because they will fail in ways that no human ever would. Additionally, when you consider how much it costs upfront to hire a team of engineers and data scientists, build a training dataset, develop the code, maintain it etc, it quickly becomes clear that except for the most costly processes internally there is no way that AI is going to be cheaper than hiring a bunch of people in India by the hour. Not to mention that the people in India can be retrained to do something in hours that would take your super specialized team of engineers months to reproduce with code.

Let's also not forget that most business processes are bespoke to each corporation. Finding a single process that can be successfully targeted across multiple companies is hard. Some people like AWS and Google are trying with Textract and some of these other AI-as-a-service products, but they're not having a lot of success. They still fail all the time.