Artificial intelligence (AI) is a rapidly emerging methodology that is impacting many areas of science and technology including the discipline of statistics. An important goal of AI is to solve complex problems as a human would. This could include the selection of statistical methods, testing of assumptions, model selection, model evaluation, model interpretation, results communication, and even statistical method development and testing. All of these areas will be important to explore as we deal with a big data world requiring an integration of computer science, mathematics, and statistics through data science to solve the most complex and impactful questions facing the world. This is a new discipline that is related to the emerging area of automated machine learning or AutoML. Examples of AutoML include the tree-based pipeline optimization tool (TPOT) and the system for accessible artificial intelligence from the University of Pennsylvania (PennAI). Examples of automated statistics (AutoStats) methods include the Automatic Statistician. We anticipate this will be a hot area in the coming years.