What does an AI governance framework include?

The seven components of an AI governance framework

A robust AI governance framework has seven core components. First, an AI use policy: a clear written statement of what AI use is permitted, what is prohibited, what verification is required before AI outputs are relied on, and who is responsible for compliance. Second, an AI inventory: a register of every AI system in use, including AI embedded in software platforms, classified by risk tier. Third, a governance structure: named individuals accountable for AI governance at board, senior management, and operational levels. Fourth, a risk assessment process: systematic evaluation of each AI system against the organisation's risk appetite and regulatory obligations. Fifth, oversight mechanisms: active monitoring of AI outputs and decisions, including the ability to detect and correct errors. Sixth, an incident reporting process: a clear procedure for identifying, escalating, and responding to AI failures. Seventh, an audit trail: documentation of governance activity that can be produced to regulators, auditors, and other stakeholders.

What the EU AI Act requires of governance frameworks

For high-risk AI, distinguish the provider's conformity and technical-documentation duties from the deployer's instructions, oversight, monitoring and record-keeping duties. Public-authority registration and Article 27 fundamental-rights assessment have specific scopes. Plan the relevant provisions against their application dates and transition rules. The organisation can use existing governance structures where they work; Article 4 does not require a new AI governance board or a particular officer title.

Legal references reviewed 4 October 2026. High-risk provisions have phased application and transition rules. Sources: Commission timetable, deployer duties, impact-assessment scope and literacy guidance.