Start with Module 1
The People Side of AI Change
- Name the adoption gap between go-live and daily use — and why closing it is a people job
- Recognise why a tool announcement can threaten status, certainty and autonomy before anyone opens the demo link
- See why AI lands differently from every technology change before it
- 01The Adoption Gap
- 02Where AI Projects Actually Stall
- 03Why AI Change Lands Differently
- 04The Myth of the Tool Reveal
- 05The Framework This Course Is Built On
Build the Plan Before You Move the People
- Write a vision specific enough that you'd know the moment you've hit it
- Diagnose where your team actually is with the AI Readiness Scorecard — before you act on guesses
- Map your stakeholders and risks with the Project Risks & Actions Report
- 01Getting Clear on Your Vision
- 02Diagnosing Your AI Readiness
- 03Plan Your Actions
What Your Team Is Actually Telling You
- Read the signal underneath silence, workarounds and performative enthusiasm — behaviour is data
- Match each of the five SCARF concerns to what the person actually needs from you
- Run conversations that open things up, and know what to do when someone won't shift
- 01The Signal Underneath the Pushback
- 02Five Things People Are Telling You
- 03Conversations That Open Things Up
- 04When Someone Won't Shift
- 05Keeping the Whole Team Moving
From Trying It Once to Making It Useful
- Create the conditions for try–reflect–adjust: low-stakes practice on real work, not more training
- Help each person find the starting points where AI saves real effort in their actual tasks
- Coach your team past the "first attempts feel off" stage with better prompting
- 01What Actually Builds Capability
- 02Finding Your Team's Best Starting Points
- 03When the First Attempts Feel Off
- 04Embedding It Into How Your Team Already Works
- 05The Habits That Make the Difference
From Rollout to Embedded
- Recognise full adoption — unprompted, varied, growing use — and measure it honestly
- Anchor the habit loop of cue, routine and reward in one task with a clear, reliable win
- Diagnose a plateau and pick the right next lever instead of pushing harder
- 01What Full Adoption Actually Looks Like
- 02Measuring Adoption Honestly
- 03What Progress Actually Looks Like
- 04When Progress Plateaus
- 05From Rollout to Business as Usual