Resource library

A short guide for boards and senior leadership teams facing AI decisions that need to be clear, owned, governed, and defensible before commitment.

Ten layers. Each is the foundation for the one above it. A practical framework for testing AI decisions before commitment and exposing hidden assumptions.

A plain-English guide to testing the decision around AI: who owns it, what evidence supports it, what risks have been considered, and whether it can be explained if challenged later.

A practical framework for leadership teams deciding which tasks AI should automate, assist or augment, and where human judgement needs to remain.

A practical tool for defining when an AI project should pause, reduce scope or redesign before cost, complexity and adoption problems grow.

A sample board pack showing how complex AI decisions become clear priorities, governed controls, accountable ownership and practical next steps.

Sector-specific briefings showing where AI is already influencing decisions, workflows and risk — and what leaders should check before it embeds.

One organisation, one AI decision, and the moment nobody created. The story behind the method, and the questions nobody asked in time. Free to download,

A board-level map of where AI sits, what it touches, who owns it, and how much governance it needs. Use it to calibrate the size of the pause to the size of the decision.

A practical ownership check for leadership teams approving AI, clarifying accountability for business outcomes, adoption, evidence, consequences and the authority to pause.

A practical leadership check for testing whether proposed AI spend is solving a clear problem, using suitable data and creating measurable value.

A seven-question framework for testing whether an AI project is clear, properly owned, defensible and ready for approval.

A practical explanation of ISO 42001 readiness, why gaps matter, and what organisations should understand before talking about audit or certification.