Leading with AI: Build Team Trust and Readiness

Course contents (12 parts)

1. 1

   Pre-course assessment

   Check your starting knowledge before learning

2. 2

   Our approach to responsible AI

   Lesson video

3. 3

   Start with a Work Problem, Not a Trend

   Choose a clear goal and connect the experiment to the team’s actual work.

4. 4

   Communicate Change Honestly

   Explain the reasons, benefits, limitations, and what remains to be learned.

5. 5

   Define Roles and Decision Authority

   Identify the users, reviewers, data owners, and approvers at each step.

6. 6

   Build Trust Through Governance

   Set data boundaries, review requirements, and a process for handling errors.

7. 7

   Measure Before Expanding

   Assess quality, workload, and impact before expanding or ending a pilot.

8. 8

   Applied case study and evidence review

   Announce an AI drafting pilot without overpromising

9. 9
   Document0 points1 min

   Course study guide

   A practical guide to the course lessons, with Thai and English editions.

10. 10
    Document0 points1 min

    Practical workbook

    Course-based exercises for review and planning a small real-world trial.

11. 11
    Document0 points1 min

    Quick reference

    A concise reference to course topics and review points for use while working.

12. 12

    Post-course assessment

    Review the key ideas from the lessons