Understand the tools.
Find your own use cases.

Start with the group’s experience and questions.

A team discovering AI assistants has different needs from people already using them to write or summarise. The first discussion establishes participants’ expectations and the situations they want to explore. It also helps choose the balance of demonstrations, exercises and discussion.

The introduction helps people understand an assistant’s output and examine its answers. The everyday-work workshop covers recurring tasks and review. The data workshop explores necessary information, access and approval points. These proposals can be discussed in your team’s context.

Prepare useful, shareable examples.

A fictional text, generic request or public document is often enough. Exercises can preserve the logic of your activity without exposing a real case. Before the workshop, we agree usable examples and access conditions for the selected tools.

The aim is to connect discovery to an understandable situation: what result is expected, how is it reviewed and what happens when it does not fit? This prepares more structured trials after the workshop and identifies needs requiring further technical scoping.