The revolutionary field of artificial intelligence (AI) has affected all aspects of our lives, including the field of chemistry. The impact of AI has been felt even more strongly in recent years, as new powerful computational tools have emerged. This review looks at the evolution of AI in chemistry, from a not-too-distant past when AI was limited to rule-based systems and simulation for simple data analyses to today's world of advanced (or powerful) machine learning. Despite the name, "advanced machine learning" refers to a highly diverse family of AI systems—most of which are not learned in the way, or with the types of data, that humans typically use to understand the world. The latest advances in AI, particularly deep learning, hold the promise of revolutionizing chemistry. The use of these advanced computational methods enables researchers to extract relationships from large datasets of molecular and chemical information. This capacity to discern pattern recognition within big data allows for the accurate prediction of molecular properties. It furthermore enables the efficient optimization of chemical reactions and the design of new materials at the molecular scale. Whether directly applied to chemistry or harnessed through interdisciplinary collaboration, AI will make a significant impact on the pace of chemical research in coming years. The review article highlights these prospects and discusses some specific areas, including drug discovery and materials science, where AI's impact will likely be felt most keenly. Moreover, AI is beginning to find applications in chemical synthesis and spectroscopy, and these have made predictions about reactions easier and enhanced data interpretation spectacularly. One of the promises going forward is the hoped-for emergence of quantum computing, which may take the not-yet-fully-realized uses of AI in chemistry even further. One of the main points made in this review is that for all this to happen, the chemistry community may need to plan a bit; interdisciplinary collaborations between chemists and AI experts will be essential to push forward the kinds of uses AI could have in our field.