Leading Your Team Through AI Adoption

What's inside

1. Level 1: What AI Adoption Really Means for a TeamFree
   Learn to tell evidence apart from hype and fear, and see what AI adoption actually changes for a team: its tasks, habits, roles and trust, not only its software.
2. Level 2: Mapping Team Work into Good and Bad Use CasesFree
   Break the team's work into tasks and sort each one as a good, risky or unsuitable AI use case, using clear criteria.
3. Level 3: Designing Small Pilots and Quick Wins
   Turn shortlisted use cases into small, time-limited pilots that have a baseline, success criteria and a stop rule set before the pilot starts.
4. Level 4: Writing a Team AI Guideline Within Company Policy
   Write a short, practical team AI guideline that sits under company policy and covers approved tools, data handling, disclosure and checking.
5. Level 5: Managing Confidentiality, Bias, Error and Shadow AI
   Identify and reduce the main AI risks in team work: confidentiality leaks, biased outputs, confident errors and unapproved shadow AI use.
6. Level 6: Training That Sticks and Building Champions
   Design role-based training that people practise on real tasks, and set up a champion network that supports colleagues without turning into gatekeepers.
7. Level 7: Talking Honestly About Jobs and Fears
   Plan and run honest conversations about what AI may mean for jobs, stating what is known, what is not yet decided and what you cannot promise.
8. Level 8: Handling Resistance and Over-Enthusiasm
   Find the different causes of resistance and of over-enthusiasm, and respond to each in a way that keeps both quality and trust.
9. Level 9: Making AI Adoption Inclusive and Accessible
   Make sure AI tools, training and new ways of working are accessible and fair for everyone on the team, including disabled, neurodivergent, part-time and less digitally confident staff.
10. Level 10: UK Employee Rights and Consultation in Outline
    Get an outline of the UK employment and data protection duties that may apply when AI changes work, and know when to involve HR, legal, unions or employee representatives.
11. Level 11: Redesigning Roles and Workloads Fairly
    Redesign roles and workloads after AI changes tasks, so that freed time and new work are shared out fairly and openly.
12. Level 12: Skills and Development Plans for Each Person
    Build an individual skills and development plan for each team member, linked to their redesigned role and their own goals.
13. Level 13: Quality Control and Accountability for AI-Assisted Work
    Set up proportionate quality checks and a clear rule that a named person is accountable for every piece of AI-assisted work.
14. Level 14: Measuring Value Beyond Usage
    Measure whether AI adoption creates real value in time, quality and customer outcomes, rather than counting logins or prompts.
15. Level 15: Protecting Morale and Wellbeing
    Watch for and protect team morale and wellbeing during ongoing AI change, including workload creep, deskilling worries, monitoring concerns and change fatigue.
16. Level 16: Reviewing and Scaling What Works
    Review pilots and decide, using evidence, whether to scale, adapt or stop each use case, and how to extend success without losing control.
17. Level 17: Final Challenge: Leading the Full Adoption Journey Exam
    Apply the whole course to a new scenario by planning AI adoption for a team from first assessment through to scaling, while keeping people's trust.

Access

The first 2 levels are free with a free account. Every level, the podcast edition and the AI tutor come with All Access at £4.99/month or any Creator plan — see pricing.

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