A Working Definition
AI governance coordinates the people, decision processes, controls, records, and oversight used to manage AI across its lifecycle. It sits above individual privacy, cybersecurity, model-risk, procurement, and compliance activities because it determines how those activities work together.
This is why a useful governance program is broader than a policy document. A policy may establish expectations. Governance also establishes who decides, what evidence is required, when issues escalate, and how an organization knows that its decisions were actually implemented.
What AI Governance Actually Governs
The scope can include internally developed systems, third-party AI services, AI-enabled product features, employee tools, and automated decision processes. The exact boundary depends on the organization, but the governance system should make that boundary explicit rather than relying on assumptions.
That makes several activities part of the same governance system:
- AI inventory and intended use;
- ownership and decision rights;
- risk classification and treatment;
- vendor oversight and change management; and
- incident handling and monitoring.
| Governance question | Operational answer | Likely evidence |
|---|---|---|
| What AI do we use? | Maintain a current inventory and scope. | System inventory, architecture records, vendor list. |
| Who is accountable? | Assign decision and system ownership. | Role descriptions, committee charters, approvals. |
| How do we manage risk? | Use a repeatable assessment and treatment process. | Risk assessments, treatment plans, issue logs. |
| How do we know controls work? | Monitor, test, and review implementation. | Logs, test results, review records, audit evidence. |
Governance Is Wider Than Compliance
Compliance answers whether a specific obligation applies and whether it has been met. Governance has to coordinate many obligations at once, including privacy, cybersecurity, contractual commitments, internal standards, and risk decisions that may go beyond the minimum legal requirement.
That is why AuditDIFF treats privacy and cybersecurity as major governance topics rather than separate universes. A single AI system can create privacy, security, safety, equality, accessibility, and operational risks at the same time.
Where Evidence Enters the Picture
Governance becomes auditable when decisions and implementation leave reliable records. Common evidence includes:
- approved procedures and inventories;
- contracts and approval records;
- logs and monitoring output;
- testing results and risk decisions; and
- public disclosures or technical validation.
The next parts of this series will examine who owns these decisions, how controls and evidence connect, and where independent assurance fits.