Agentic AI refers to AI systems that pursue goals autonomously — planning multi-step tasks, using tools, and taking actions with limited human oversight, rather than only responding to a single prompt.
How it works
An agentic system pairs a reasoning model (often a large language model) with the ability to plan, call tools and APIs, read and write data, and evaluate its own progress. Instead of returning one answer, it breaks a goal into steps, acts on each, checks the result, and adjusts — looping until the objective is met or it hands back to a human.
Why it matters for enterprise AI
For enterprises, agentic AI is the shift from AI that advises to AI that executes — completing workflows across systems rather than drafting text a person still has to action. Realising that value depends on the surrounding guardrails: grounding in company data, governance over what agents may do, and monitoring, so autonomy stays reliable and auditable.
