AI agents: AI agents: agent, chatbot and workflow compared.
What an AI agent is, how it differs from a chatbot and a workflow, which tasks it can take on, and which limits and approval steps are needed.
In short: A chatbot answers, a workflow runs fixed steps, and an agent handles a task. It reads, checks, decides on intermediate steps, uses tools and asks a person at defined points.
From an answer to a completed task.
An agent receives a goal (“handle this enquiry”), not a question. It uses tools – search, knowledge system, ERP, calendar – decides on intermediate steps and keeps track of its state. At defined points, it obtains approval.
Its strength lies in recurring, clearly defined tasks. Judgement, negotiation and responsibility stay with people. This is not a limitation but the condition for reliability.
Chatbot, workflow, agent.
| Chatbot | Workflow | Agent | |
|---|---|---|---|
| Input | Question | Trigger | Task |
| How it works | one answer | fixed steps | decides on intermediate steps |
| Tools | none | defined actions | tools after approval |
| State | none | per run | across the whole task |
| Approval | – | rarely | at defined points |
When an agent makes sense.
- Task is recurring, clearly defined and can be solved with tools → agent.
- Fixed steps without interpretation → defined workflow.
- Information only → chatbot or knowledge system.
- Before launch: define approval points and tool limits for the tested scope.
What this article is based on.
- Own project experience at Swiss AI Labs with Swiss AI Agents; no external study
Products, Labs and case studies.
Frequently asked questions: AI agents
What are the risks of agents?
Permitted tools, data access and approvals must be defined before use and checked in a test run.
Which model does an agent use?
Routing decides this per task – based on capability, data protection, cost and availability.
Have a specific process assessed.
The AI potential assessment examines the benefits, prerequisites and risks of the process.