AI Agents vs Chatbots: What's the Difference?

Two products described as “chatbots” can do very different jobs. One might guide visitors through a menu, while another retrieves business information and updates a customer record. Before comparing proposals, ask the provider to demonstrate the exact task, explain which systems it connects to and show where a person takes over.

Can a chatbot use AI and take actions?

Yes. A scripted chatbot follows predefined branches, but an AI chatbot can interpret natural language, find relevant information and call connected tools. For example, it could answer a service question, collect enquiry details or request a booking. Those capabilities depend on its integrations and permissions; a chat interface alone tells you very little about what it can do.

Flipside’s Always On website assistant covers approved business answers, enquiry capture and booking-page links. Reading live availability or confirming a booking inside another system requires an additional integration. Our custom action chatbots are scoped around those connected workflows.

When does the workflow need an AI agent?

An agent is useful when the next step depends on context: finding missing information, choosing an approved tool or checking whether an action succeeded. A fixed workflow is often enough when the sequence is known in advance. Anthropic’s guide to building effective agents distinguishes predefined workflows from systems where the model directs the process, and recommends starting with the simplest approach that works.

Neither approach needs unlimited autonomy. Define the records it may read, the changes it may make and the decisions a person must approve. An agent does not automatically learn from every conversation: retaining history, updating its knowledge and changing a model are separate capabilities that need deliberate design.

Scripted chatbot, AI chatbot or custom agent?

Scroll sideways to compare all three options.

A worked example: handling a website enquiry

If a visitor asks which service fits their business, an assistant may only need approved service information and a link to your enquiry form. If it must check an existing customer record, look up availability and create a booking, you need connected tools and explicit permissions. That sequence could still be a fixed workflow; it only needs agent behaviour when choosing the next step requires additional context.

This is an illustrative design example, not a client result. Before launch, test an unknown customer, an unavailable appointment and a failed connection. The system should explain an incomplete action and hand over with the collected details, rather than claim a booking succeeded.

How should you choose?

Write down the task, approved information, required actions and human handover first. Use our first AI project checklist to turn that into a brief, then test the workflow before launch. If the task needs context from several systems, explore custom AI agent development. More autonomy is useful only when it improves the job and your team can verify the result.