The buzz around Artificial Intelligence (AI) can’t seem to stop these days. AI is used as an umbrella term to refer to all sorts of computational methods that allow machines to perform specific tasks automatically. However, 99% of research and efforts fueling the current AI boom are concentrated in a sub-field known as Machine Learning (ML). ML is a very powerful technique to perform specific tasks more efficiently. It can be a game changer for specific and well-defined applications. Its successful utilization requires not only deep expertise in AI/ML algorithms, but also strategic vision, knowledge about business processes, and understanding of human skills. Risks and limitations do not negate the potential of AI/ML, but they highlight the importance of understanding AI/ML well to use it properly. Using AI requires thinking. Simply applying AI on a messy problem without understanding it is a guarantee for an expensive failure. The purpose of AI is not to replace humans, but to be a tool humans can use to become better at their jobs.