Now that We've Got AI What do We do with It? - DataScienceCentral.com

Summary: Whether you're a data scientist building an implementation case to present to executives or a non-data scientist leader trying to figure this out there's a need for a much broader framework of strategic thinking around how to capture the value of AI/ML. There are many articles written from a tools perspective about how to take advantage of specific capabilities of AI. Those encompass for example chatbots from NLP or image classification based on CNNs. To be clear, I'm talking about the expanded definition of AI that should more correctly be called AI/ML since the more mature field of machine learning is full of good implementation lessons ranging from marketing to fraud to forecasting. But whether you're a data scientist building an implementation case to present to executives or a non-data scientist leader trying to figure this out there's a need for a much broader framework of strategic thinking around how to capture the value of AI/ML.