Machine Learning (ML) represents a powerful augment for the modern surgeon. Through the lifecycle of a surgeon-patient relationship, ML can help improve care before, during, and after an operation. Before surgery, it can help surgeons pick the right surgery for the right patient and create an effective operative plan. During surgery, it can prevent a surgeon from accidentally cutting important structures and help them reconstruct complex anatomy from smaller incisions. After surgery, it can predict which patients will need closer follow-up. A future where every step of a surgeon’s patient encounter is improved with ML is not far away. They are hurdles, however, and innovators will have to find comprehensive, high-quality data, navigate regulatory oversight, and overcome physician bias.