This presentation will provide real world case studies of applying A.I. and machine learning based analytics to motor and drive components. We will present the methodology of how to apply predictive monitoring with success stories from deployed solutions and documented ROI. Three case studies will be presented, including: servo-motor and ball screw health monitoring on CNC machine tool applications; electric motor health monitoring with traction motor and stator winding degradation; as well as bearing failure prediction, that being the most common failure of electric motors. We will summarize the current challenges and new developments in this field and how you can start deploying AI-based analytics rapidly and systematically, in your operations.