Whenever we are set to improve something, what is the first thing we do? If you are thinking of assessing the past, you are correct. It is the most convenient and sure-shot method of understanding improvement areas and fixes that are required for better future outcomes.
This should be no different for AI implementations as well. Automation and primitive forms of AI have been in trial and operation for many years. Some have worked as expected and some not so much. I have chosen a few use cases that have failed or have not shown full expected benefits.
These case ...
