MAST Consulting Group · 8 September 2026 · Implementation perspective
Define what needs review
Identify outputs that can influence customers, employees, financial decisions, security or external communications. Set review requirements according to the consequences of an incorrect output.
Give reviewers a practical checklist
Ask reviewers to check accuracy against reliable source material, confirm that confidential data is handled appropriately, assess whether the output is suitable for its audience, and identify unsupported claims. A fluent response is not evidence of correctness.
Provide an escalation route
Reviewers need a clear way to reject an output, request expert review or pause an activity. Document who handles uncertainty and who owns the final business decision.
Retain proportionate evidence
Record approval for consequential outputs without collecting unnecessary personal or confidential information. Use recurring errors to improve guidance, training and tool configuration.
Put it into practice.
Explore the AI governance toolkit or discuss your organization’s next step.