Create a Minimum Viable AI Governance System

Governance should make responsible decisions easier, not bury low-risk work in the same process as consequential systems. Start with a visible inventory and controls that increase with impact. This decision connects to Build an AI Strategy That Starts With Business Value and Turn Company Priorities Into an AI Opportunity Portfolio, which provide the strategic direction and portfolio context. Use this four-part leadership framework Inventory — Record every AI use case, owner, purpose, data, vendor, users, and status. Risk tiers — Classify uses by consequence, data sensitivity, autonomy, scale, and detectability. Required evidence — Match testing, review, approval, monitoring, and documentation to the tier. Lifecycle — Define change review, incident response, periodic reassessment, and retirement. A practical decision example A low-risk internal drafting aid requires approved tools, prohibited-data rules, user review, and registration. A system influencing credit or employment requires specialist review, stronger evaluations, notice, appeal, and executive approval. This is a hypothetical example; use your own baseline, constraints, and evidence. Evidence, governance, and responsible use Use the NIST AI Risk Management Framework to connect the initiative to governance, context, measurement, and ongoing management. The companion NIST AI RMF Playbook turns those functions into questions leaders can assign and review. The GAO AI Accountability Framework is useful for examining governance, data, performance, and monitoring across the system life cycle. Compare the plan with the OECD AI Principles, particularly transparency, robustness, accountability, and respect for people affected by the system. For generative AI, review the NIST Generative AI Profile and test representative cases using OpenAI’s evaluation guidance. Use the OWASP Top 10 for LLM Applications to discuss application threats before a model can access sensitive information or take actions. Check performance statements against the FTC’s guidance on AI claims, and review information handling with the FTC’s privacy and security resources. For a broader organizational management approach, study the ISO/IEC 42001 overview. Take this to the next leadership meeting Create a governance table with risk tier, examples, prohibited uses, required owner, data review, testing, approval, monitoring, incident route, and reassessment frequency. Record the owner, evidence source, decision date, and what would cause the company to stop. The goal is not to make the document look complete. The goal is to make the next decision explicit, measurable, and accountable. Continue with Map AI Risk Across Four Business Areas. Use Run a Quarterly AI Portfolio Review: Keep, Fix, Scale, or Stop to revisit the decision with current evidence.