By Antonio Giarrusso, founder of Userbot and Head of AI at the smeup group · November 2026
An AI agent is an artificial intelligence system that doesn’t just answer: it carries out tasks inside business processes and systems, such as opening a ticket, updating an order or booking an appointment. It works within set rules and permissions, logs every step and hands over to a person when needed.
A chatbot and an agent are not the same thing.
| Chatbot | AI agent | |
|---|---|---|
| What it does | Answers questions | Carries out tasks: opens tickets, updates orders, creates records |
| Where it works | In the chat | Inside business systems: ERP, CRM, ticketing |
| When it stops | When it can’t answer | When a rule says so, and it hands over to a person |
| How it’s controlled | By rereading conversations | With permissions, a log of every step and explained decisions |
Where they already work.
With Userbot we have put AI agents into production in front of customers and citizens. For ENEA the assistant handles 97% of messages about home renovation incentives; for CupSolidale 94% of conversations about healthcare bookings are closed with no human intervention; at Miflex Digital Humans support operators on the factory floor. All the numbers are in the case studies.
How to put them into production.
- 1Choose a process, not a technologyA repetitive task with high volumes and clear rules: customer requests, internal tickets, bookings, technical support.
- 2Define what the agent can doWhich systems it can read, which actions it can take, within which limits. Everything else goes to a person.
- 3Connect company knowledgeProcedures, manuals, documents: the agent must answer and act based on them, not on what it knows about the world.
- 4Plan the handover to a humanThe agent must know when to stop and pass the case to an operator, with all the context.
- 5Measure and expandHow many requests it closes on its own, how fast, with what satisfaction. Then you add specialized agents that work as a team.
Agents that work as a team.
The next step is orchestration: specialized agents working together, with one agent routing requests, shared memory, context handover and escalation to people. That’s what Userbot 3.0 does, as covered by Data Manager. Every decision an agent makes comes with a readable explanation, so it can be checked and corrected. Agents are also one of the areas for which Userbot is cited in the 2026 Gartner® Hype Cycle™ reports.
For the full picture, from Shadow AI to governance, see the guide AI adoption in companies.
Have a candidate process?
Tell me which one: I’ll reply myself, or the Userbot team will.
Frequently asked questions.
What is an AI agent?
An artificial intelligence system that doesn’t just answer: it carries out tasks inside business processes and systems, within set rules and permissions, and hands over to a person when needed.
What’s the difference between an AI agent and a chatbot?
A chatbot answers. An agent acts: it updates an order, opens a ticket, books an appointment. That’s why it needs more controls: permissions, logs and the ability to explain every decision.
What does orchestrating multiple agents mean?
Having specialized agents that work together: one routes requests, others handle different areas, with shared memory and context handover, and escalation to people when needed.