In a recent episode of the McKinsey & Co. podcast, McKinsey Global Institute partner Michael Chui explains the role that simulation plays in training AI: To more deeply understand why this is, we can think of machine learning and simulation as being two different approaches for understanding and predicting the behavior of complex adaptive systems. Individually they are both powerful modeling paradigms, but it is together, working in concert, that they show the greatest promise. Machine learning automates the building of analytical models. The models are constructed using algorithms that learn from data. These algorithms are able to update models in real-time, giving them the ability to generate real-time predictions.