Insights
How to Audit an AI Policy
A practical guide to testing whether an AI policy is well designed, understood, implemented, monitored, and enforced across the organization.
Hallucinations: From AI Error to Business Risk
AI hallucinations are not just model errors: they can affect processes, decisions, reporting, customers, and audit evidence.
How to Test AI Inventory Completeness
An AI inventory is not proven complete by reviewing it. Test it against procurement, SaaS, expenses, system records, and targeted surveys.
AI, Machine Learning, and Generative AI for Auditors
A practical taxonomy of AI, machine learning, and generative AI that helps auditors identify the risks, controls, and evidence that matter.
RAG Explained for Internal Auditors
How RAG connects LLMs to enterprise knowledge, why citations matter, and what auditors should test across sources, retrieval, access, and outputs.
When Human Oversight Actually Works
Human oversight controls AI risk only when reviewers can understand, challenge, intervene, and leave evidence of the decisions they make.