AI-Native Workforce Foundations

Programme outline

1. 01

   How AI changes the nature of work — not just which tasks

   The difference between AI as a productivity tool and AI as a workflow partner — and why this shift requires a different set of skills, not more of the same ones.

2. 02

   From task execution to intent-setting, judgment and supervision

   What your new role looks like when AI handles more of the execution — how to set intent clearly, when to push back, and what good supervision actually requires.

3. 03

   Understanding what your AI tools are actually doing

   A practical guide to demystifying the AI tools you use — what they can and cannot see, how they generate output, and why the same prompt can yield different results.

4. 04

   When to trust AI output and when to verify

   A decision framework for AI trust — by output type, by stakes, by domain — so you can calibrate verification effort without second-guessing every AI-assisted task.

5. 05

   Your role in maintaining Cognitive Coverage

   What Cognitive Coverage means at the individual level — visibility into what AI is doing, ability to verify outputs, and the responsibility to flag when something doesn't look right.

6. 06

   Escalating and flagging AI errors: making it a team norm

   Why raising an AI error is a contribution, not a complaint — how to flag effectively, what good escalation culture looks like, and how teams build shared standards over time.

7. 07

   Building your AI-native work habits: a 30-day plan

   A structured personal practice for developing AI-native judgment — daily habits, reflection checkpoints and a template for tracking your own calibration over the first 30 days.