Gartner defines agentic analytics as software used for the process of data analysis that applies AI agents across the data-to-insight workflow, orchestrating tasks semi-autonomously or autonomously toward stated goals that support, augment or automate insights. Agentic analytics’ must-have capabilities are data source connectivity, data preparation, agent workflow orchestration, automated insights and natural language query. Optional capabilities include data storytelling, a coding assistant, function calling, agent memory, embedded analytics and platform administration. Agentic analytics is the evolution of augmented analytics through the application of AI agents to data analysis. Must-have capabilities are: data source connectivity data preparation agent workflow orchestration automated insights natural language query Optional capabilities include: data storytelling a coding assistant function calling agent memory embedded analytics platform administration
Augmented analytics uses AI to automate analytics workflows in platforms, contextualizing user interfaces with automated insights, generative storytelling explanations and collaborative exploration. Driven by machine learning (ML) and generative AI, augmented analytics enables natural language queries and personalized analytics catalogs. It democratizes advanced analytics with augmented data ingestion, data preparation, analytics content and DSML model development. It also curbs human biases and accelerates insights for diverse users.