The AI Meeting Governance Framework provides a structured approach for governing AI-generated meeting records throughout their lifecycle—from conversation to trusted business record.
Rather than focusing solely on AI technology, the framework defines the governance practices needed to ensure that AI-generated transcripts, Minutes of Meeting and follow-up actions can be trusted as organizational records.
The framework is built on five interconnected governance domains.
1. Meeting Risk Classification
Not every meeting carries the same level of business risk. Governance requirements should be proportionate to the impact of the meeting and the decisions it contains.
2. Evidence and Traceability
Trusted meeting records must remain connected to the evidence from which they were created, including recordings, transcripts, AI-generated outputs and verification history.
3. Verification Workflow
AI-generated meeting records should pass through a defined verification process before becoming trusted business records.
Conversation → Transcript → AI Minutes → Verification → Trusted Business Record
4. Accountability
The framework defines clear ownership for reviewing, approving and maintaining AI-generated meeting records. AI may assist the process, but accountability remains with the organization.
5. Governance Maturity
Organizations can progressively strengthen AI meeting governance, moving from unverified AI summaries to enterprise-governed, evidence-based business records.
Governance Maturity describes an organization's journey from simply using AI to establishing trusted, governed AI-generated business records.
| Level | Description |
|---|---|
| Level 1 – AI Generated | AI creates transcripts and meeting summaries with little or no governance. |
| Level 2 – Human Reviewed | People review and correct AI-generated records before they are used. |
| Level 3 – Evidence Verified | Records are verified against the original meeting evidence through a defined verification process. |
| Level 4 – Enterprise Governed | Verification is embedded in organizational governance with policies, accountability, traceability and auditability. |
As AI increasingly creates organizational knowledge, governance must extend beyond the AI model itself to the information the model produces.
The AI Meeting Governance Framework provides a practical foundation for ensuring that AI-generated meeting records are accurate, traceable and accountable before they become part of organizational memory.
It begins with a simple governance question:
Who Verified This?