Training
AI only pays off for teams that know how to work with it.
With AI, everyone saves time on their own task. But the company gains little.
The gap does not come from the technology: it comes from the way people work together. Nobody has learnt how to hand a task to an AI, check its work, or tell it no.
The way of working together
- up to 70%on a single task
- around 4%1across the whole company
We train your teams on their own files, not on textbook examples.
They leave knowing how to do it, not just having understood it.
Four tracks
For leaders
- Who it is for
- The managing director, and those who decide with them.
- What we do
- Understand what AI changes in your line of business, what it will never do, and where it will make you gain. No jargon.
- What you leave with
- A clear view of what you hand to AI first, and of what you keep.
For teams
- Who it is for
- People who already use AI, or are about to.
- What we do
- Use AI every day, with method: ask well, check, know when not to use it.
- What you leave with
- Sound habits, practised on their own files.
For working with your workers
- Who it is for
- People who receive a worker's work every day.
- What we do
- Read what the worker has prepared, approve or correct it, and change a rule yourself, in plain language.
- What you leave with
- The right move for every decision, and a hand on the rules.
Throughout the subscription
- Who it is for
- Your teams, for as long as the subscription runs.
- What we do
- AI changes every week; your teams do not fall behind. With every change, they learn what is different and what it gains them. How the engine evolves
- What you leave with
- What changes for you, explained with every change.
What your teams gain
- They do not put up with AI; they direct it.
- They keep control of every decision.
- They spend less time on what does not need their judgement, and more on what does.
A conventional course, and ours
- A conventional training course is forgotten within a month.
- Ours happens on your real work, and it continues for as long as AI moves forward.
The tool changes nothing. Your teams change everything.
Sources
- ILO, The Aggregation Paradox of AI, C. Chan and K. Shedania, May 2026. The 4% comes from an EIB working paper covering more than 12,000 companies; “four companies in five” from a survey of nearly 6,000 executives in more than 20 countries (Yotzov et al., 2026), both cited by the ILO.↑