Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learning (ML, a set of learning techniques used by AI) have the capacity to revolutionize the delivery of patient care. This essay examines the mechanics and processes of machine learning through discussion of deep learning and natural language processing and then discusses the application of these learning techniques in pattern recognition of malignant tumors in comparison to present methods of diagnostic imaging assessment. The discussion also covers the implications of AI assistive technology more broadly regarding ethical policy making, patient autonomy, and the healthcare Iron Triangle of cost, quality, and access. It concludes with the idea that failure to incorporate AI and ML techniques in healthcare may be malpractice.