Chatbots focus on conversation
Traditional chatbots help answer questions, guide visitors and collect information. Some use fixed decision trees; others use language models and knowledge search. The common goal is a useful conversation within a defined scope.
Agents can act on tools
An AI agent may reason about a goal and choose from permitted tools, such as searching approved documents, creating a support ticket or reading a calendar. This introduces more possibilities but also more failure modes than simple question answering.
Autonomy should match the risk
An assistant that drafts a response can usually be supervised easily. A system that edits customer records, sends emails or triggers financial actions requires explicit permissions, approval points, logs and rollback strategies. A tool-using agent should not be assumed safe merely because it sounds confident.
Ground answers in reliable information
Whether building a chatbot or agent, carefully scoped knowledge retrieval, current data, validation and clear uncertainty handling matter. Measure accuracy on realistic tasks instead of relying only on appealing demonstrations.
Start with the smallest reliable solution
Choose a chatbot when answering and routing are sufficient. Introduce tool use only when there is a clear operational benefit and strong controls. The simplest system that consistently solves the problem is often the best investment.