Guide
The world of AI Agents
Understand, compare, choose — the guide for business owners in French-speaking Switzerland.
By Samuel Lavado · Published 3 September 2026
What is an AI Agent?
An AI Agent is an autonomous software system that carries out concrete tasks on behalf of a business owner: qualifying a new contact, replying to a client, sorting an email, blocking a slot in a calendar — by directly accessing the tools you use every day (email, calendar, client records) and chaining several steps together without human intervention.
It is not a tool that waits for your instructions at every step. It is a digital colleague that reasons from your documents and your business rules, plans the actions required, carries them out, then reports back to you on the result.
Its autonomy is always limited: it acts within a precise scope that you control. When a situation falls outside that scope — an unusual request, an ambiguous case, an emotionally tense client — the AI Agent pauses and hands you the full context. The aim: to keep errors and frustration to a minimum.
If you run a law practice, a real estate agency, a construction company or a service business in French-speaking Switzerland, an AI Agent can take on a significant share of the administrative tasks that keep you from focusing on your real work.
Conventional chatbot, conversational assistant, AI Agent: what is the difference?
The term “chatbot” has become blurred: it can refer to a conventional chatbot (a program that follows a predefined scenario, also called an FAQ bot) or to a general-purpose conversational assistant. These are very different technologies. Here is a more useful distinction.
| Conventional chatbot (FAQ bot) | Conversational assistant | AI Agent | |
|---|---|---|---|
| How it works | Follows a predefined script | Generates natural-language answers | Reasons, plans and carries out actions |
| Understands context | No — recognises keywords | Yes, but may make up an answer if information is missing | Yes — understands your business context and checks your data before answering |
| Handles the unexpected | No — gets stuck outside the script | Partly — answers, but cannot act | Yes — finds a solution or hands over to you |
| Accesses your tools | No | Not by default | Yes, if you allow it — calendar, email, client records |
| Chains tasks together | No | No — one answer at a time | Yes — plans and carries out several steps |
| Relies on your data | No | No (except manual copy-paste) | Yes — consults your documents and your history |
| Logs its actions | No | No | Yes — actions and decisions are traceable |
Conventional chatbot (FAQ bot)
How it works
Follows a predefined script
Understands context
No — recognises keywords
Handles the unexpected
No — gets stuck outside the script
Accesses your tools
No
Chains tasks together
No
Relies on your data
No
Logs its actions
No
Conversational assistant
How it works
Generates natural-language answers
Understands context
Yes, but may make up an answer if information is missing
Handles the unexpected
Partly — answers, but cannot act
Accesses your tools
Not by default
Chains tasks together
No — one answer at a time
Relies on your data
No (except manual copy-paste)
Logs its actions
No
AI Agent
How it works
Reasons, plans and carries out actions
Understands context
Yes — understands your business context and checks your data before answering
Handles the unexpected
Yes — finds a solution or hands over to you
Accesses your tools
Yes, if you allow it — calendar, email, client records
Chains tasks together
Yes — plans and carries out several steps
Relies on your data
Yes — consults your documents and your history
Logs its actions
Yes — actions and decisions are traceable
A conventional chatbot answers questions that were planned in advance. “What are your opening hours?” → pre-programmed answer. If the question falls outside the script, it goes round in circles or points to a form. Useful for a basic FAQ, limited as soon as the conversation becomes real.
A conversational assistant is built on an LLM (Large Language Model — a language model trained to understand and generate text). It understands natural language and answers relevantly, but it only answers: it does not check your calendar, send an email on your behalf, or qualify a contact according to your criteria. And when information is missing, it may produce a plausible but false answer — without warning you.
An AI Agent combines the same type of LLM with access to your tools and the ability to act, from the outset. A potential client writes to you at 10 pm with a complex request? The AI Agent understands the request, checks your availability, qualifies the contact according to your criteria and offers them a slot — without any input from you. If the request falls outside the intended scope, it notifies you instead of improvising. Before answering, it consults your internal documents using RAG (Retrieval-Augmented Generation — in plain terms: it looks up the information in your own files before forming its answer, rather than making it up).
How does an AI Agent work, in practice?
An example of a standard AI Agent. It follows a six-step cycle with every interaction:
MentilAI deployment strategy
Before deployment, MentilAI carries out an audit of your client communication processes. The AI Agent is built on the basis of this audit, validated together. Its scope of action is documented in a configuration specification: tasks covered, default operating mode, actions classed as sensitive that require your approval.
Once validated, the AI Agent goes into production with two possible modes:
Co-pilot
The AI Agent analyses and proposes; you approve before anything is carried out. Default mode during the start-up phase, to build confidence gradually.
Autonomous
The AI Agent carries out validated tasks on its own within its scope. Actions classed as sensitive stay under your control.
You choose which mode applies to each type of task, and can adjust it at any time. A review is planned at the end of the start-up phase to assess the switch to autonomous mode for eligible tasks.
The precise commitments — timelines, scope of action, level of traceability — are set out in the configuration specification specific to each project.
In short
No technical skills required. You receive an operational AI Agent, tested on your real cases. You move from “I approve” to “I delegate” — at your own pace, within a clear framework.
AI Agents configured by sector
Every sector has its own workflows, regulatory constraints and client expectations. A high-performing AI Agent is not a generic tool applied to your trade — it is a configuration built around you that reflects your rules, your vocabulary and your priorities.
MentilAI configures AI Agents for four business sectors in French-speaking Switzerland:
Legal
Document follow-ups, sorting of enquiries: fewer back-and-forth exchanges, files that are more complete by the first appointment.
Real estate
Financial qualification, follow-up of viewings: serious enquiries are handled first, even outside office hours.
Construction
Technical pre-qualification, scheduling of visits: unrealistic enquiries are filtered out before the site visit.
Services
Bookings, flow management: no more lost bookings during busy periods.
These proposals give a direction. In the end, you define the role of your AI Agent — according to your priorities, your constraints and the reality of your day-to-day work.
Does one of these sectors sound like yours?
45 minutes to understand your needs and explore the possibilities.
What an AI Agent does not do
An AI Agent is not infallible. Hallucinations (answers that seem correct but are not) still occur. In a survey cited by Microsoft Research (2025, p. 18), 40% of employees surveyed said that, in the previous month, they had received AI-generated content that looked useful but turned out to be incomplete or inaccurate. That is why MentilAI AI Agents are designed with safeguards: human validation of critical actions, a defined scope of action, traceability of decisions.
An AI Agent does not replace your judgement. It does not make strategic decisions for you, and does not handle situations that call for empathy, creativity or a fine reading of human relationships. It does not negotiate a property mandate and does not argue cases in court.
The AI Agent is designed to handle routine requests reliably. For complex situations, it prepares the ground and hands over to you — your client notices no drop in the quality of the exchange.
The question is not “will AI replace my profession?” The useful question is: “Which repetitive tasks cost me time that I could spend on what really gives my expertise its value?” That is exactly the logic of delegating the invisible.
What the data says
+448%
increase in AI job postings in the United States since 2018, against −9% for non-AI IT roles
Job postings published in the United States, 2018 to 2025, UMD-LinkUp AIMaps data (University of Maryland), cited by BOND.
88%
of early adopters report a positive ROI on at least one use case
Survey of 3,466 business leaders worldwide, 2025, for Google Cloud.
62%
of organisations are already experimenting with AI Agents (23% are deploying them at scale, 39% are testing them)
McKinsey's annual global survey of executives and managers, November 2025 edition.
40-60 min
saved per day and per user of AI tools
Microsoft Research, 2025 — p. 17
Time reported by ChatGPT Enterprise users surveyed (Chatterji et al., 2025), cited by Microsoft Research.
These figures come from international studies on varied populations. They do not automatically apply to every Swiss business owner: results depend on the sector, the volume of enquiries, the quality of the data available and the rigour of the implementation. In practice, ROI appears when you target a specific flow — for example sorting incoming enquiries, qualifying contacts and booking appointments.
Data protection and Swiss law
The FADP (Swiss Federal Act on Data Protection — the Swiss law, based on the same principles as the European GDPR) applies directly to any processing of data by AI. The FDPIC (Federal Data Protection and Information Commissioner) is clear:
Your clients must know whether they are dealing with a machine — and to what extent their data is used.
For more information, see our MentilAI privacy policy.