At a recent CA conference utilities and other industry folk considered the growth of AI/machine learning in energy deployment. Topics included having more sensors at the grid edge, reasons for implementing AI/ML (including more efficiency and productivity, greater resilience and anomaly detection, etc.), and core challenges facing customers like aging infrastructure, rise in cyber threats, changes in generation profiles skewing toward renewables, and load growth.