AI governance is how an organization decides who uses AI, for what and under which controls, and these articles show how to make it hold up under audit.
Most companies don’t stall on what AI can do. They stall when a security review, an auditor or the board asks for proof that the models are safe and controlled, and there’s no evidence beyond screenshots. When AI shapes credit, care or a legal argument, a wrong decision costs more than a slower rollout.
Start with the practitioner’s playbook for an audit-ready AI risk assessment. Other pieces cover adding models to a risk register built for applications, AI for regulatory compliance, and moving from pilot to production.
Good governance leaves a trail: what was asked, what the model answered and who checked it before anyone signed off. In Suprmind, five frontier models check each other’s answers in one conversation, and the Master Document turns that conversation into a deliverable a reviewer can read.
