NIST AI RMF: A Practical Starting Point for Product Teams
You do not need a 200-page policy to begin AI governance. Start with inventory, use-case risk tiers, and measurable guardrails.
The NIST AI Risk Management Framework is voluntary—but customers and partners increasingly ask how you govern AI in production. The framework's Govern, Map, Measure, and Manage functions give structure without requiring certification on day one.
Begin with an AI inventory: models, APIs, data sources, features, and owners. You cannot manage risk you have not named. Include third-party LLMs and embedded vendor AI, not just internally trained models.
Tier use cases by impact. A internal summarization tool and a customer-facing recommendation engine do not warrant the same scrutiny. Align testing, monitoring, and approval workflows to tier.
Define measurable guardrails: allowed data classes, human review triggers, fallback behavior, and incident response when outputs violate policy. Documentation beats aspirational principles.
Integrate AI governance with existing GRC—privacy, security, vendor management—not as a parallel program. Your SOC 2 or ISO controls already cover access, change management, and vendor risk.
Review quarterly as models, vendors, and regulations evolve. AI governance is a lifecycle discipline, not a one-time legal review before launch.