An AI agent doesn't just answer questions — it can take multi-step actions using tools. Here's the difference between a chatbot and an actual agent, and when each makes sense.
A chatbot answers a question with text. An agent can use tools — query a database, call an API, send an email, update a record — to actually complete a task across multiple steps, deciding along the way what to do next based on what it finds. The distinction matters because a chatbot is a feature; an agent is closer to a worker.
Modern AI agents are given a defined set of 'tools' — functions they're allowed to call, like 'look up customer by email' or 'create a ticket' — along with a description of what each one does. The agent reads the task, decides which tools it needs, calls them in sequence, and reacts to what comes back.
An agent that can take action also needs explicit limits: which tools can it call, under what conditions does it escalate to a human, and what happens if it's uncertain. Without these guardrails, an agent will eventually do something costly with full confidence.
Lead qualification against defined criteria, first-pass drafting of customer responses for human review, document processing and data extraction, and monitoring/alerting tasks are all areas where agents reliably add value today without needing to be perfect.
If a task has only one or two steps and doesn't require tool use, a single AI call (or no AI at all) is usually cheaper and more reliable than building a full agent.