The shortest useful distinction
Responds to questions or prompts in a conversation.
Runs predefined rules when known conditions occur.
Pursues a defined task using approved information, tools and boundaries.
Coordinates agents, systems and human decisions across a repeatable process.
When a chatbot is enough
A chatbot is appropriate when the primary need is conversational access to information: answering common questions, explaining a policy or helping someone find a resource. It becomes risky when a conversational interface is mistaken for an operating process and users assume the answer has been verified or authorized.
When traditional automation is better
Traditional automation is often the best choice for stable, deterministic work. If a rule can be written clearly and exceptions are rare, a conventional integration or workflow may be faster, cheaper and easier to test than an AI agent.
Examples include moving a file after approval, sending a notification when a status changes or copying known fields between systems.
When an AI agent adds value
An agent becomes useful when the work involves interpretation, unstructured information or variable preparation. It can read documents, identify requirements, compare evidence, highlight gaps and draft a structured output. That flexibility must be paired with clear limits.
Use the least complex system that works
Question or explanation? Start with a chatbot.
Stable rule and predictable input? Use traditional automation.
Variable knowledge work with a defined output? Consider a focused AI agent.
Several connected stages and approval points? Consider an agentic workflow.
Multiple specialized workflows across a larger process? Consider an AI workforce only after smaller capabilities prove useful.