Agentic AI refers to AI systems that can autonomously take actions to achieve a goal — planning steps, using tools, and executing multi-step tasks — rather than only generating a single response. Agents are built on large language models but add memory, tool use, and decision loops.
How it works
An AI agent uses a language model as its reasoning engine, then loops: it observes a goal, plans, calls tools or APIs, observes the result, and repeats until the task is complete. This lets it do things like book travel, triage tickets, write and run code, or operate other software — actions, not just text.
Why it matters
Agentic AI is the defining enterprise trend of 2026: 23% of organizations are already scaling agentic systems, but Gartner projects more than 40% of agentic AI projects will be canceled by 2027 amid governance and ROI challenges. See Enterprise AI Statistics 2026.
Related terms: Large Language Model · Retrieval-Augmented Generation · All glossary entries