AI data analysis is revolutionizing how data teams work by automating repetitive tasks and enabling users to obtain insights through natural language interactions. This approach utilizes artificial intelligence to streamline data analysis workflows, allowing business users to type questions in plain English and receive detailed, contextually relevant answers, complete with visualizations and SQL code. AI data analysis encompasses three main areas: AI-augmented code-based analysis for faster coding by data scientists, natural language exploration for business users, and deeper exploration of existing data artifacts. Platforms that integrate these areas, like Hex, offer a unified workspace where data scientists and business users collaborate seamlessly, maintaining governance and consistency across various interfaces. This integration allows for conversational self-service analytics, accelerating analysis from concept to output and enhancing cross-functional collaboration. AI analytics platforms vary in their approach and maturity, with some focusing on business user self-service and others on technical depth. Effective implementation involves starting small, scaling based on value, and establishing governance to manage self-service expansion. As organizations adopt AI analytics, they can expect improved decision-making, reduced workload for data teams, and enhanced strategic focus.