Advances in machine learning algorithms and computing power have fueled a rapid increase in artificial intelligence research in health care, including mechanical circulatory support. In this review, we highlight the needs for artificial intelligence in the mechanical circulatory support field and summarize existing artificial intelligence applications in 3 areas: identifying patients appropriate for mechanical circulatory support therapy, predicting risks after mechanical circulatory support device implantation, and monitoring for adverse events. We address the challenges of incorporating artificial intelligence in daily clinical practice and recommend demonstration of artificial intelligence tools’ clinical efficacy, reliability, transparency, and equity to drive implementation.