Bring a task people recognise
Choose a task that matters to the participants. Leaders might compare options for a business decision. A service team might draft a response to a common question. People should recognise a useful answer and know what is missing.
Prepare fictional, anonymised or otherwise approved examples. Explain which tools and information the team can use, with clear instructions they can follow after the workshop.
Practise checking as well as asking
Have participants create a draft, check it and improve it. Ask them to spot unsupported claims, missing information and changes they would make before using it.
Compare two attempts at the same task. What changed when the instructions became clearer? What still needed a human decision? Keep the discussion tied to their work.
Leave with a short working guide
Turn the exercise into a guide: the task, information needed, an example instruction, checks to make and when to ask for help.
Keep it easy to find and short enough to use during the task. The team should know what to do next without searching a slide deck.
Make time to use the learning
Agree on one task to try afterwards, who will support the team and when you will compare notes. Ask what people actually used, where they got stuck and what they changed. Attendance alone does not tell you whether the learning helped.
If the exercise did not carry over to the job, adjust it. The aim is a team confident enough to check and question AI’s work as well as use it.
Put it to work
Before planning the agenda, finish this sentence: after the session, our team should be able to…
- Which everyday task will we practise?
- How will participants check whether the output is useful?
- Who will help them apply it after the workshop?
What would help your team use AI?
Tell me who’s learning and the work they do. In a free 30-minute chat, we can explore whether a talk, practical workshop or guided sessions would help.
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