Step-by-step AI governance guides for practitioners: build the program, meet regulations, audit AI systems, and manage AI vendors.
What you should know before letting an AI vendor into your organization, with the questionnaire, evidence list, risk-rating method, contract clauses, red flags, and reassessment checklist to do it.
AI Vendor Risk Management: Due Diligence, Contracts and Monitoring Read More »
Which AI rules apply to you, and what do you need to do about them? A practical guide to the EU AI Act, ISO/IEC 42001, NIST AI RMF and U.S. state AI laws, mapped from requirement to action, owner, and evidence.
AI Compliance Guide: EU AI Act, ISO 42001, NIST AI RMF and U.S. AI Laws Read More »
A step-by-step AI audit procedure, from scoping and information requests to testing, sampling, and writing findings, with specific guidance for chatbots, RAG, agents, predictive ML, and foundation models.
How to Audit an AI System: A Practical Guide. Read More »
Practical guide · Build · Version 1.0, October 2026 An AI governance framework is the set of roles, policies, processes, and controls an organization uses to decide which AI it uses, how that AI is built or bought, and how its risks are managed over time. A good one is not a document. It is
AI Governance Framework: A Practical Guide Read More »