AI workshop checklist.
Prepare to practise.

1. Agree a useful brief

Begin with a specific outcome. Instead of “be more productive with AI,” describe a task participants should be able to complete and review. That gives the trainer a basis for selecting relevant examples.

• Identify who is attending and what they do at work.
• Describe their current AI experience, including any differences within the group.
• Choose two or three priority tasks.
• Agree what a useful result should contain and how it will be checked.
• Confirm the group size, available time and delivery arrangements.

A short brief is enough to start. The training categories can help you decide whether the priority is foundations, workplace productivity or creative content.

2. Prepare suitable examples

Examples should be realistic enough to make the exercise meaningful and simple enough to inspect during the session. A short fictional document can often support a better learning activity than a large, complicated file.

• Use fictional, public or appropriately anonymised material.
• Remove names, personal data and confidential details that are unnecessary for the exercise.
• Keep a copy of the original source so participants can compare it with the output.
• Identify the facts that must remain unchanged.
• Agree how missing information should be marked rather than invented.

For example, a meeting-notes exercise can include decisions, assigned actions and unanswered questions. Participants can then judge whether an AI-generated table preserves those distinctions.

3. Arrange approved tool access

Avoid discovering account or network problems after the exercise starts. Confirm the tools the organisation allows and discuss the exact access needed with the trainer.

• Make sure participants have a suitable device and reliable connectivity.
• Check account access before the session.
• Confirm whether any exercise depends on a paid feature or file-upload capability.
• Check organisational restrictions on websites, extensions and document uploads.
• Keep the agreed source files and task brief easy to find.

Tool interfaces and available features can change. Confirm the practical requirements for the agreed workshop rather than relying on a general product list.

4. Give the practice a review standard

Participants need more than a prompt to copy. Give them a clear task and a way to judge whether the response meets it. Ask them to explain their refinements.

• Check the output against the purpose and audience.
• Compare facts with the supplied source.
• Look for omissions and unsupported assumptions.
• Review tone, structure and format.
• Record one change that improved the result and why it helped.

Read about my demonstration, practice and review approach for a fuller explanation of this learning sequence.

5. Choose a small follow-up task

Before the workshop ends, identify one approved task participants can repeat. Save the inputs, useful instructions and review steps together, so they can reconstruct the process later.

At the follow-up, compare the result with the original goal. Ask what worked, what needed editing and what still felt uncertain. Use that evidence to decide whether the team needs more practice, a different example or a more advanced topic.

A completed draft is one output. Being able to explain the process and check its result is the skill you want to develop.