Artificial intelligence (AI) has arrived and it will directly impact how we assess, monitor, and manage inflammatory bowel diseases (IBD). Advances in the machine learning methodologies that power AI have produced astounding results for replicating expert judgement and predicting clinical outcomes, particularly in the analysis of imaging. This review will cover general concepts for AI in IBD with descriptions of common machine learning methods including decision trees and neural networks. Applications of AI in IBD will cover recent achievements in endoscopic image interpretation and scoring, new capabilities for cross-sectional image analysis, natural language processing for automated understanding of clinical text, and progress in AI-powered clinical decision support tools.