Guide
For people deciding what AI should do in their organisation. Reflections and working materials with sources you can follow.
Who maintains the knowledge your AI uses?
A practical guide to reliable definitions, ownership and current knowledge, using a capacity-planning example and a small maintenance agreement.
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Verify AI outputs: sources, omissions and contradictions
A traceable review for summaries and decision briefs. Includes precise references, checks for missing information and two copyable working instructions.
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Evaluate AI pilots: quality, effort and value
A practical process for leaders: define one task, compare representative cases and count the complete effort required to produce a usable result.
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AI agents: define permissions and approvals
Which actions may an AI agent take? A guide to bounded assignments, technical permissions, approval points and verifiable execution.
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An AI learning session that rehearses the next decision
An adaptable learning sequence for healthcare and business: form a judgement, use assistance, work through a new case and assess learning again later.
ReadWhen AI becomes unavailable: prepare for continuity and vendor exit
A guide for leaders to define minimum operations, identify dependencies and rehearse recovery using a fictional case. Includes preparation for a provider change.
ReadMaintaining shared AI instructions: test changes and preserve versions
A practical maintenance agreement for shared AI instructions: purpose, test cases, changes, approval and returning to an earlier version.
ReadWhen people and AI disagree: resolve the disputed decision
An adaptable procedure for organisational decisions: define the disagreement, check authoritative information and record the cause for future cases.
ReadEnding an AI initiative while preserving what was learned
How leaders can compare continuing, pausing, redirecting and ending an initiative, with clear next commitments and an orderly handover.
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