Although recent scientific studies suggest that artificial intelligence (AI) could provide value in many radiology applications, much of the hard engineering work required to consistently realize this value in practice remains to be done. In this article, we summarize the various ways in which AI can benefit radiology practice, identify key challenges that must be overcome for those benefits to be delivered, and discuss promising avenues by which these challenges can be addressed.