Abstract: A system and method for automating the training of enterprise customer response systems using a range of dynamic or generic data sets, used to gradually take human supervision and intervention out of the training process for enterprise WA and similar automated response engines, by training existing machine learning models or engines using a heuristic middleman annotation assistant that helps map generic/public/new datasets to the existing machine learning model or engine, and allowing for limited human oversight over the remaining unknown or badly classified data segments which is used to further teach the heuristic and classification model until the human oversight is no longer needed for the heuristic to learn and map newer datasets, thereby reducing human, dollar, and time costs, and improving automated response system efficiency.