Governance
AI Policy Framework
An AI policy framework is the formal set of rules, standards, and processes that govern how an organization develops, procures, deploys, and retires AI systems. It translates high-level governance principles into operational requirements — covering acceptable use, data handling, bias testing, human oversight, and incident response.
A credible AI policy framework answers six questions for every AI deployment: What is the system allowed to do? Who approved it? What data can it access? How are outputs reviewed? What happens when it fails? How is it retired? Organizations without written policies are exposed to shadow AI deployments that bypass compliance controls entirely.
Related terms
- AI Governance — AI governance is the system of policies, controls, and accountabilities that determines what AI is allowed to do inside an organization, who approves AI deployments, how AI decisions are audited, and how risk is managed.
- Responsible AI — Responsible AI is an umbrella term for the operational practices that make AI deployments safe, fair, transparent, accountable, and aligned with human values — covering ethics, governance, security, privacy, and reliability across the full lifecycle.
- NIST AI RMF — The NIST AI Risk Management Framework (AI RMF) is the US voluntary framework for managing AI risk, organized around four core functions: Govern (policies and culture), Map (context and risk identification), Measure (analysis and assessment), and Manage (prioritization and treatment).
- EU AI Act — The EU AI Act is the world's first comprehensive legal framework for artificial intelligence, adopted in 2024 and phased in through 2027.