Adoption is a change in work, not a training event.

Choose a real task to practise

Begin with a task people recognize. Explain the intended improvement, show an appropriate use of AI, and make time to practise. Keep the learning close to the decisions, documents, and conversations the team already handles.

Make the rules usable

People need clear answers about which tools they can use, what information they may enter, and who reviews the output. Put those answers next to the workflow, with a named person to contact when the situation does not fit the guidance.

• Leadership: Explain the purpose and make space for learning in the work schedule.
• Practice: Use realistic exercises with permitted information and review the results together.
• Responsibility: Clarify who validates outputs and remains accountable for decisions.
• Feedback: Offer a simple route to report poor results or confusing guidance.
• Measurement: Look at usefulness, quality, and sustained use alongside participation.

Learn from non-use

When people do not adopt a tool, investigate the reason. The workflow may be unclear, the output may require too much correction, or the task may not benefit from AI. Treat those observations as input to the design.

Build a review rhythm

Agree when the team will review its experience and who can change the approach. Discuss examples of useful work, errors, and unresolved questions. Update the workflow and learning materials together so practice and guidance stay aligned.