AI governance and compliance insights.
Articles, checklists, and operating guidance in this category.
What is AI governance? Definition, components, and frameworks
AI governance is the operating model that lets a company know which AI systems exist, what risk they carry, who owns them, and what proof shows they are controlled.
AI governance vs AI compliance: what is the difference?
AI governance is the operating system for responsible AI decisions; AI compliance is the proof that selected obligations and controls were met.
The five components of AI governance: discover, comply, govern, secure, audit
A complete AI governance program needs discovery, obligation mapping, decision workflows, runtime controls, and audit-ready evidence working together.
How to build an AI governance program in 30 days
A 30-day AI governance program should produce a living inventory, risk tiers, approval paths, minimum controls, and a first evidence package.
AI governance checklist for regulated teams
Regulated teams need an AI governance checklist that ties every system to ownership, risk, controls, monitoring, and evidence before production use.