What is an AI Agent?
An AI agent is a software entity that uses an AI model to perceive context, make decisions and take actions through tools in pursuit of a defined role — for example a sales agent that qualifies leads and books meetings, or a finance agent that prepares pricing and validates quotes. Unlike a general chatbot, an agent has a specific job, specific system access, and defined limits on what it may do.
The anatomy of a business-grade AI agent
A production agent is more than a prompt. It combines:
- A role and persona — what the agent is responsible for and how it communicates.
- Tools — typed, validated actions it can take (send email, update CRM, generate document).
- Context — organizational memory: the customer history, the price list, the process state.
- Budgets and rate limits — caps on model usage and action frequency.
- Guardrails — rules about what it must never do, and when it must escalate to a person.
Single agents vs an agent workforce
One agent automates a task. A workforce of specialized agents — organized by business function like a real org chart — automates processes: a website engagement agent captures a lead, a sales agent qualifies it, an executive assistant schedules the meeting, and a project agent opens the delivery workflow. Coordination between them is what requires an orchestration layer, often called an agentic control plane.
Frequently asked
- How is an AI agent different from an automation or RPA bot?
- RPA replays fixed steps and breaks when reality deviates. An agent reasons about context and chooses actions within its permissions, so it handles variation — while approval gates keep consequential steps under human control.
- Can AI agents work together?
- Yes — through shared memory and a message bus with priorities and hand-offs, coordinated by an orchestration layer. That is how multi-step, multi-department processes are executed.
