AI training for business teams and managers.

The usual shape: a morning of slides, a few impressive demos, general examples from somebody else's industry. Afterwards everyone returns to their desk and carries on as before, because nobody built the bridge from the demo to their own work.

The difference is not the tool, it is the material. Someone who spends the session working on their own quote, their own e-mail and their own meeting notes leaves with something that is still true the next day. So you bring the tasks, and we work on those — not on sample data.

For the people who work with text, documents and decisions all day: administration, assistants, sales, project management, leadership. In other words most of a company, not the IT department.

Developers are explicitly not the audience. Not because they have nothing to learn, but because they would need a different session — and because mixed groups mean half the room is bored while the other half is left behind.

• Workshops for business teams, assistants and leadership
• Exercises on your own work, not on sample data
• Clear rules about what may go in and what may not
• Follow-up until it sticks in day-to-day work

A round runs half a day to a full day, depending on how much of your own material comes with it. The lecture portion is deliberately small: a brief, honest framing of what these tools actually do well and where they reliably fall over — enough to correct expectations without burning the morning.

The rest is work on your own cases. Everyone brings two or three recurring tasks: the quote that looks much the same every week, the meeting notes nobody enjoys writing, the pile of incoming requests that has to be sorted. We practise on those, and we keep going until the output is good enough for real use — not just until the demo worked.

What you leave with is a short page written together: what proved worth it, what did not, and the data rules from the section above. That page goes up in the team afterwards, and it is the real return on the day.

The most important half hour of any session is the one about data. What may be typed into a tool that runs outside the company? What absolutely may not? How does someone tell the difference day to day without having to ask every time?

Without those rules one of two things happens. Either nobody uses the tools, because everyone is afraid of getting it wrong. Or everybody uses them and nobody thinks about it. Both are worse than a clear line, agreed in the team, that fits on one page.

The weeks after a workshop are where most of the value normally leaks away. It helps if someone follows up: what actually made it into daily work? Where is it stuck? Which task turned out to be a worthwhile candidate that nobody thought of during the session?

Often that second round reveals that some of what people now do by hand with an AI tool every day could be automated properly, once. At which point the training turns into an automation question — and the other way round.