Insights
Prompting, RAG and Agents: What Changes
Prompting, RAG and AI agents may use the same underlying model, but they create different value, risk, control, and audit surfaces.
Prompt-Based Auditing: A Practical Introduction
A practical guide to turning structured prompts into reproducible behavioral tests for generative AI applications.
Mapping AI Frameworks Without Creating Complexity
A practical architecture for combining the AI Act, ISO/IEC 42001, NIST, COSO, and IIA sources without duplicating controls, evidence, or audit work.
Auditing Model Risk Without Being a Modeler
Generalist auditors can assess model governance, validation, monitoring, and ownership without reperformance of specialist technical testing.
How to Audit Third-Party AI Governance
A practical audit approach to AI vendors: due diligence, contracts, model changes, incidents, monitoring, audit rights, and exit readiness.
Writing Strong AI Audit Findings
Learn how to connect criteria, condition, cause, risk, and action so AI control gaps become clear, defensible, decision-useful audit findings.