An increasingly connected world and the Big Data generated by it have made household names out of terms and acronyms describing data analysis. Chief among them is artificial intelligence (AI), which generally refers to the ability for a computer to reason. In the context of industrial systems, this typically means predictive maintenance and proactive response to machine behavior. The interconnectedness of data—much of it generated from the Internet of Things (IoT)—and AI cannot be overstated. I can’t remember the last time I heard about IoT without also hearing about AI. This is particularly true with Industrial IoT (IIoT), where systems often stream more information to the cloud than most—some send entire protocol registers directly to the cloud in real-time. As product companies in the IIoT space attempt to move from merely connected machines to truly smart machines, they face both technical and business hurdles. In the blog below, we’ll discuss a few of these hurdles. Namely, if product manufacturers can do AI, how do they implement that intelligence and what is the end user experience?