Machine learning (ML) has a surprise, too. One of the biggest misconceptions about ML deployment within organizations is comprehending the difficulty and the value. Integrating ML into your business workflows can be broken down into five activities. Optimizing an ML algorithm takes much less relative effort, but collecting data, building infrastructure, and integration each take much more work. The differences between expectations and reality are profound. Not every problem has an ML-powered solution, but many do, and even those that do not will benefit from this journey.