The choice depends on what should happen after the user’s question. A chatbot provides a conversational interface, an automation follows defined steps, and an AI agent can select actions and tools within an objective. These components can work together. A useful decision starts with the task, information and responsibility.
A business may ask for “a website bot” when its real need is to give a colleague complete context for an inquiry. Another may simply need answers that are easier to find. Naming the technology does not define the work.
Which distinction matters to the business?
Here, automation means a workflow with defined steps and conditions. An agent means a system where the model can choose tools to pursue an allowed objective. Anthropic’s guide to agents explains this distinction. A chat interface does not necessarily have autonomy.
| Need | Approach to evaluate | What to verify |
|---|---|---|
| Send a form to the CRM | A rules-based integration | Does the information arrive correctly and once? |
| Answer questions about an offer | A conversational interface with approved information | Is the answer supported by the current offer? |
| Summarize differently written inquiries | AI within a reviewed workflow | Are facts and unknowns preserved? |
| Choose between several possible next steps | An agent with defined tools and limits | Can it choose appropriately and verify the outcome? |
For a simple task, a rule may be easier to operate and inspect. When language varies across requests, assisted interpretation may be useful. Autonomy is a design choice that needs a purpose.
A conversation does not establish that an action happened
In a hypothetical example, a visitor asks whether they can visit a showroom on Saturday. An answer about opening hours may be enough. If they want an appointment, the system needs to check availability and record the selected time.
“You’re booked” is not proof that the operation succeeded. For this process, we would show confirmation only after a valid response from the scheduling system. If the integration fails to respond, the booking would remain unconfirmed and an alternative would be offered.
This distinction affects cost, testing and responsibility. An assistant explaining public information and one changing records in a system require different controls.
What needs to exist around the model?
The offer, information sources and commercial rules must be identifiable. For each action, we define the required data, permission, expected outcome and response to failure.
The team needs to see what happened and continue manually when necessary. Who reviews a prepared brief? Where does a response to a clarification question go? Who takes over when a colleague is unavailable? These questions define a substantial part of the solution.
When does a conversational experience make sense?
When people’s questions and circumstances benefit from clarification. Product selection may depend on available space and intended use. A B2B request may depend on timing and requirements already documented elsewhere.
Visitors should also be able to browse and contact the team directly. Some know exactly what they need and prefer to compare options themselves. We would make conversation a useful choice and test where it helps, while keeping essential information accessible.
How can you start with a manageable scope?
Choose one need and a bounded journey. Define what the system receives, what it may do and which outcome must be verified. Test ordinary inquiries, ambiguous ones and situations where it should ask for help.
Several roles on a diagram do not automatically require multiple agents. Preparation, checking and handover can belong to one workflow. Additional components should be justified by results and the ability to operate them.
At NOT MORE., we can clarify the choice, build the experience and integrations, and provide agreed monitoring. We can also deliver only the missing component of a process that is already defined.
What should the system do for the customer and the team beyond holding a conversation?