[ Training and the AI Act ]
We have to train our people on AI. What does that mean in practice?
The AI Act asks those who use AI systems to make sure people know what they are using. Training stops being optional.
The point
The AI Act moved training from good practice to requirement: whoever puts AI systems in people’s hands has to make sure those people know what they are using, with which limits and which risks.
In practice that means little theory and a lot of your own work: what can be uploaded, how to read an answer, when to trust it and when to check. Plus a record of what was done, because an obligation you cannot demonstrate counts as one you did not meet.
What it covers
- Paths by role, on the company's own documents and cases
- What can go inside an assistant and what cannot, with examples taken from your work
- How to read an answer: the source, the doubt, when checking is needed
- What changes for the people who decide, and who answer for choices made with a system's help
- A record of what was done, because an obligation also has to be shown
How we work
- 01 We look at who uses what Roles, tools already switched on, and where AI is already coming in without anyone having decided it.
- 02 We write the paths One per role, short, on the company's cases instead of generic examples.
- 03 We deliver, and the record stays In a room or remote, on real files. At the end you know who did what and when, which is for you and for the day someone asks.
Where we have already done it
The skills involved
- Adoption
- Governance
[ Let's talk ]
Tell us what you want to build.
We take care of the team. You do not need a specification: just tell us what you want to achieve, whether that is a process that should run on its own or an answer someone looks up by hand today, and which environment you work in.
A thirty minute call. If the project is not for us, we'll say so.