Why businesses using machine learning should not ignore "concept drift"

BUSINESSES often think that machine learning (ML) models learn on their own and get better over time. If organizations want to use the technology effectively in 2020, they need to understand why and what to do about it. Business leaders have been told that they need a mountain of data to train any artificial intelligence (AI) or machine learning model. As a result, much of their efforts in the past year have been focused on acquiring data. However, once the models are deployed, they stop evolving and fail to account for changes that occur in variables.