Definition
Agentic AI
Agentic AI describes systems that can plan steps, use tools and pursue a goal across multiple actions with limited human prompting.
Short definition
Agentic AI is an approach where an AI system does more than answer a single prompt. It can break a goal into steps, call tools, inspect results and continue working until it reaches a stopping condition.
Many agentic systems are built around large language models, tool APIs and orchestration logic.
How it works
An agent usually receives a goal, creates a plan, chooses tools and evaluates intermediate outputs. Tools can include search, databases, code execution, calendars, ticketing systems or business applications.
The most important design choice is control. Some agents only suggest next steps, while others can act directly. Higher autonomy requires stronger guardrails, logging and permission boundaries.
Example
A sales operations agent could inspect CRM records, identify stale opportunities, draft follow-up emails and create tasks for account owners. A safer version would ask for approval before sending anything externally.
Why it matters
Agentic AI is attractive because it can automate workflows, not just generate text. It also raises risk: tool misuse, data leakage, hidden errors and runaway actions are all possible if the system is poorly constrained.
Useful agents are usually narrow, observable and permission-aware. They should solve a specific workflow and leave an audit trail.