Courses/Leadership & Management/Working with AI: Delegating, Reviewing and Staying Accountable
Working with AI: Delegating, Reviewing and Staying Accountable
A scenario-based e-learning course on delegating to AI without handing over the judgement.
Overview
A scenario-based e-learning course that treats AI as a delegation problem rather than a software one: what to hand over and what to keep, how to brief it properly, how deeply to review what comes back, and where accountability stays regardless. In production. It will ship as a scenario-based, self-paced e-learning course: a SCORM 1.2 package for your LMS, with completion tracking.
Format. Self-paced, scenario-based e-learning. SCORM 1.2 — upload it to your LMS and completion tracks automatically.
Who it is for. Any organisation that wants to run this as self-paced learning; suitable for employees at any level.
What learners take away
- Decide which tasks to hand to an AI assistant — and which to keep — using stakes and checkability.
- Write delegation-grade briefs using the five-part BRIEF structure: Background, Result, Inputs, Edges, Format.
- Review AI output in three passes, at a review depth set before reading.
- Recognise automation bias and fluency effects, and design review habits that assume drift.
- Keep accountability where it belongs: own outcomes, disclose AI use, and respond to errors by fixing workflows rather than blaming the last pair of eyes.
- Set five checkable personal working rules and, for managers, one team norm for AI-assisted work.
Course outline
Frames AI as a delegation problem rather than a software problem: what changes when work goes to a machine, what never transfers, and why AI capability is jagged rather than general.
Two questions — stakes and checkability — drive the Delegation Grid. Participants map eight of their own recurring tasks onto it and identify the work that stays human on principle.
Why thin briefs produce confident rubbish, and the five-part BRIEF structure — Background, Result, Inputs, Edges, Format — practised by rewriting a weak brief and swap-testing it with a neighbour.
Automation bias and fluency effects, then the method: three review passes at a depth set before reading. The flagship exercise seeds six flaws in a realistic AI output for trios to find.
Where accountability sits when machines do the work, the moral crumple zone, disclosure norms inside and outside the organisation, and a group case study — international or GCC version by audience.
Participants convert the session into five checkable personal rules — and, for managers, one team norm to propose — with a thirty-day follow-up check built into the workbook.
What you get
SCORM 1.2 package
A self-contained course you upload straight to your LMS — no installation, no dependencies.
Completion tracking
Reports status and completion back to your LMS like any SCORM course.
Scenario-based
Learners make real decisions inside a workplace story and see what each choice costs.
Per-organisation license
Host it for unlimited internal learners — one-time purchase, no per-seat or renewal fees.
The license in one sentence
Buy once and host the course on your own LMS for unlimited internal learners — no per-seat and no renewal fees. You may not resell or redistribute the SCORM package itself. Full license terms
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