AI
A chatbot answers questions. An agent can take actions: looking things up, updating records, completing steps. The difference is permissions, and permissions are where the risk sits.
Chatbot
AI Agent
A chatbot grounded in your documentation is a retrieval problem: find the right passage, answer from it, cite it, escalate when confidence is low.
It is comparatively safe because the worst failure is an unhelpful answer.
An agent decides what to do next and acts.
That is far more useful and introduces a category of failure a chatbot cannot have: a confident, incorrect action against real data. Whether that matters depends entirely on what it is permitted to touch.
The practical rule is to scope by reversibility.
Reading data, drafting a reply for approval, classifying a request: cheap to get wrong. Issuing refunds, changing records, sending external communication unsupervised: expensive, and appropriate only with narrow permissions and an audit trail.
Most businesses should start with the chatbot shape and add actions individually as each proves reliable.
Starting with a broadly-permissioned agent is how the first serious incident happens before anyone has calibrated their trust.
Usually the chatbot shape: grounded answers with escalation. Add actions one at a time as each proves reliable, rather than granting broad permissions before anyone knows how often it is wrong.
Irreversible or regulated ones without human approval: payments, contractual commitments, external communication that cannot be retracted. Reversibility is a better test than complexity.
A chatbot answers questions. An agent can take actions: looking things up, updating records, completing steps. The difference is permissions, and permissions are where the risk sits.
You have read what we think. If you want to know what it means for your case specifically, describe it and we will tell you which parts of chatbot vs ai agent actually apply — and which do not.
