AI Checklists

Check whether your AI strategy has clear business priorities, executive ownership, investment logic, governance requirements and measurable outcomes.

Review whether your organisation has the ownership, decision rights, controls, oversight and lifecycle processes needed to govern AI consistently.

Identify common AI risk areas across data, privacy, security, bias, reliability, operations, regulation and organisational reputation.

Test whether a proposed AI use case has a clear business need, suitable data, defined ownership, realistic value and manageable risk.

Confirm that an AI initiative has clear scope, accountable ownership, suitable data, required capabilities, governance controls and success measures before work begins.

Review the key questions organisations should ask before selecting an AI supplier, platform, model provider or technology partner.

Check whether the data supporting an AI initiative is accessible, appropriate, well governed, sufficiently reliable and suitable for its intended use.

Review the critical controls, approvals, testing, monitoring and operational safeguards that should be considered before an AI system goes live.

Check whether an AI system has sufficient evidence, testing, documentation, controls and ongoing monitoring to support confidence in its operation.

Check whether your organisation’s AI policies cover the practical rules, responsibilities, approved uses, prohibited uses and escalation routes employees need.

Review whether employees and managers have the guidance, skills, communication, support and confidence needed to adopt AI responsibly.

Help boards challenge AI strategy, investment, risk, governance and assurance by focusing oversight on the questions that matter most.