AI Agent
Last Updated: September 10, 2026 | By Mihail Sebastian | AI Dictionary
A system that perceives its environment, decides what to do, and acts to reach a goal – from simple rule-based programs to systems that learn and adapt.
What is an AI Agent?
An AI agent is a system that runs a loop: it perceives its environment, decides what to do, and acts – then perceives the result and goes again. Agents range from simple rule-followers to systems that learn and adapt with experience.
The term names the system itself; the broader design approach of building AI that pursues goals autonomously is called agentic AI.
Types of AI Agents
- Reactive agents respond directly to what they sense, with no memory of the past: the same input always produces the same response.
- Deliberative agents keep an internal model of their environment and plan ahead, weighing future consequences before acting.
- Learning agents improve with experience, adjusting their behavior based on what worked and what didn’t.
Applications of AI Agents
- Customer service: Chatbots that resolve routine queries (order status, password resets, refunds) and escalate to a human only when they get stuck.
- Autonomous vehicles: Self-driving cars whose sensors perceive the road, whose planner decides the maneuver, and whose controls execute it, many times per second.
- Smart assistants: Systems that handle scheduling, reminders, and home automation with minimal supervision.
Example of an AI Agent
A robotic vacuum cleaner is the perceive-decide-act loop in miniature. Its sensors detect walls, furniture, and drop-offs (perception); it picks a cleaning path and reroutes around obstacles (decision); and it drives that path (action), then senses the new position and repeats.
No one steers it: given the goal of a clean floor, it works out the rest.
Related AI terms: Agentic AI · Reinforcement Learning · Chatbot · Robotic Process Automation · ROS · Tool Calling
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