This session presents a practical architecture for governing decision systems supported by artificial intelligence (AI) in regulated organisations. Using a realistic enterprise case, such as AI-assisted recruitment screening, credit risk support, insurance claims triage, or customer service escalation, Glen Rai will show how an organisation can move from informal AI adoption to a structured governance model.The session will guide participants through a step-by-step method for mapping AI influence, assigning ownership, categorising risk by tier, designing human oversight, setting review gates, managing vendor dependencies, and building an evidence ledger that can support audits, assurance, and internal accountability. The emphasis is on implementation: what should be documented, who should be accountable, when a system should be reviewed, and how governance can be maintained after deployment.Participants will leave with a reusable decision-system canvas, risk-tiering criteria, a governance-gate model, an evidence-ledger structure, and a 90-day roadmap for initiating AI governance in their own organisations.The session will also briefly reference TIRA, an emerging implementation layer developed from this architecture, showing how these governance steps can be translated into a structured workflow for AI inventories, risk reviews, evidence capture, and readiness reporting.This is a how-to session for organisations that need AI governance to become practical, repeatable, and capable of withstanding audits, scaling effectively, and operating under real-world pressure.