# Chatbot vs. AI agent: what sets Databot apart from traditional bots

> A chatbot answers. An AI agent takes action. The difference seems small, but it changes everything: it quotes, schedules, hands off and recommends without human intervention.

- Published: October 8, 2024 (2024-10-08)
- Category: Product
- Source: https://databot.cl/en/blog/chatbot-vs-agente-ia

## Key takeaways

- A traditional chatbot follows fixed flows; an AI agent understands natural language and context.
- The agent uses tools: it quotes, schedules, creates tickets and hands off to a person with full context.
- Flows are still useful for regulated processes; the best approach combines them with an agent.

For years, "chatbot" meant a menu with buttons: *press 1 for sales, 2 for support*. It worked for the basics, but any question outside the script ended in frustration.

AI agents change that logic. The difference comes down to one sentence: **a chatbot answers; an agent takes action.**

## The traditional chatbot

- Follows **predefined flows** (decision trees).
- Recognizes keywords, but **does not understand context**.
- When the question does not fit the flow, it **hands off or gets stuck in a loop**.
- Every new case means **designing a new flow**.

## The AI agent

- **Understands natural language**, even with typos or long messages.
- Answers with **your business information** (documents, website, catalog).
- **Uses tools:** queries systems, creates tickets, schedules appointments, captures leads.
- **Decides when to hand off** to a person and passes along the full context.

[Imagen: Databot platform diagram: data sources (Shopify, VTEX, documents and APIs), AI configuration with instructions, knowledge and tools, intelligent chat and actions such as sales, scheduling, tickets and human handoff]

*How an AI agent works in Databot: it connects to your data, is configured with instructions and tools, answers with real information and takes action.*

## What "taking action" means

With the Databot Tools Manager, the agent does more than chat; it acts:

- **Quotes:** takes the customer's information and generates a quote.
- **Schedules:** checks availability and books the appointment.
- **Hands off:** creates a ticket in the ticketing system or transfers to a rep based on rules.
- **Recommends:** suggests products based on what the customer is looking for.

![The agent takes a quote request and, if the customer prefers to talk to a person, hands them off to an agent with full context.](https://databot.cl/assets/dev/img1.jpg)
![The agent takes a quote request and, if the customer prefers to talk to a person, hands them off to an agent with full context.](https://databot.cl/assets/dev/img15.jpg)

## When does a flow still make sense?

Flows are not going away. They are useful when the process **must** follow exact steps, for example, to verify identity or meet a legal requirement. The ideal approach is to combine them: flows for regulated processes and an AI agent for everything else.

## In summary

| | Chatbot | AI agent |
|---|---|---|
| Understanding | Keywords | Natural language and context |
| Knowledge | Hand-written answers | Your knowledge base |
| Actions | Limited to the flow | Tools and integrations |
| Maintenance | Redesigning flows | Adjusting instructions and content |

Learn more about [AI agent configuration](https://databot.cl/en/plataforma/prompt-manager) or [book a demo](https://databot.cl/meeting).