Agentic AI

Agentic AI refers to systems that plan multi-step actions, call external tools, and operate with some autonomy toward a goal, rather than producing a single response to a single prompt.

What is Agentic AI?

An agentic system pairs a language model with a tool registry, a planning loop, memory, and an exit condition. The model decides which tool to call, observes the result, and continues until the goal is reached or a budget is hit. Patterns include ReAct, plan-and-execute, multi-agent orchestration, and supervisor-worker. Agentic systems are powerful but harder to evaluate, debug, and constrain than single-shot calls. Production deployments wrap them with guardrails, budget caps, action allow-lists, and human approval gates.

How does Agentic AI apply to enterprise AI?

Enterprises deploy agentic AI for ticket resolution loops, claims handling, sales follow-up, internal research, and any workflow that requires multiple tool calls. The EU AI Act treats some agentic behaviours as higher risk because actions affect external systems.