A chatbot that informs or an agent that resolves?
The market uses the two terms as synonyms, and they aren't: one converses about the task, the other carries it out. Choosing wrong in either direction is expensive. This guide gives you the criteria to decide with your real case.
Talking about the task is not doing the task
"Where is my order?" has two possible answers. The chatbot explains how to check the status; the agent checks the order and tells you where it is. The second one is what the customer wanted.
Converses and informs
- Answers questions from your documentation (RAG), citing its sources
- Resolves the bulk of repetitive queries: opening hours, policies, product questions
- Escalates to your team with context when the conversation needs it
- Contained risk: its worst mistake is giving bad information, and with cited sources it is auditable
- Fast to put into production: it does not require deep integrations with your systems
Executes and resolves
- Does everything the chatbot does and also acts: looks up, creates and modifies data in your systems
- Closes complete transactions: order status and changes, appointments, bookings, sign-ups and cancellations
- Follows defined processes with minimal permissions and confirmation for sensitive operations
- Higher risk: its worst mistake is executing the wrong action; it demands reversible actions and full logging
- Requires real integration with your CRM, ERP, helpdesk or booking system
Four questions that decide for you
This is not a technology decision but an operational one: what your customers ask for, what systems you have and how much risk you can execute.
What share of your queries are transactions?
Audit a month of tickets. If most are information questions ("how long does shipping take?"), a chatbot solves the problem. If a relevant share are transactions ("swap my size"), the chatbot will only postpone the frustration: it will explain beautifully how to make the change the customer wanted you to make for them.
Do your systems have APIs?
An agent needs to touch your systems safely: look up the order in your ecommerce, move the appointment in the calendar, issue the credit note in billing. If your operations live in tools without APIs (or in spreadsheets), the right order is chatbot now and agent once the integration becomes possible.
What happens if the action goes wrong?
Classify your transactions by reversibility. Checking a status: no risk. Rescheduling an appointment: reversible. Issuing a refund: irreversible and costly. A well-designed agent starts with reversible actions and leaves irreversible ones behind human confirmation. If your entire case is irreversible actions, the agent may not be worth it yet.
Do you already have a chatbot that works?
The agent inherits everything from the chatbot: curated documentation, scope, escalation. If your current chatbot already fails at conversing, giving it the ability to execute actions multiplies the problem, it does not solve it. First a solid, measured conversational foundation (with real metrics, not just deflection), then the hands.
Torn between the two options? We'll tell you — using your real tickets.
Free audit →It's not "either/or": it's a three-stage path
Hardly any serious project chooses between chatbot and agent forever: it starts by informing, learns from real conversations and gradually gains the ability to act where the data justifies it.
An assistant that informs
A chatbot with RAG over your curated documentation, cited sources and escalation to your team. It resolves the bulk of informational queries and, above all, generates the data you don't have: what your customers actually ask for and how much of it is transactions.
First safe actions
With the conversations as evidence, the assistant gains read-only and reversible actions: checking order status, availability, appointments. Integration with your systems with minimal permissions and a log of every action.
An agent that resolves
The highest-volume transactions get executed end to end: changes, bookings, sign-ups. Sensitive operations behind confirmation, everything auditable and with real resolution metrics, not deflection. The assistant no longer talks about the work: it does it.
Dive deeper into each stage: AI chatbot for business, AI agents and our AI assistant by sector.
Chatbot vs AI agent: common questions
What is the difference between an AI chatbot and an AI agent?
Which do I need first, a chatbot or an agent?
Is an AI agent riskier than a chatbot?
Can I turn my current chatbot into an agent?
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