Override and Escalation Procedures
Document the procedures, authority levels, and logging requirements when humans reject, modify, or escalate AI-generated decisions.
Objective
Ensure that human overrides are captured, attributed, and fed back into the governance process rather than disappearing without trace.
Maturity Levels
Initial
Overrides happen informally with no documentation or escalation path.
Developing
Some teams log overrides informally; escalation paths are not consistently defined.
Defined
A documented procedure specifies how to override an AI decision, what to log, and when to escalate to a higher authority.
Managed
Override patterns are analyzed to identify systematic model errors or process failures.
Optimizing
Override data directly informs model retraining, prompt refinement, and governance policy updates.
Evidence Requirements
What an auditor or assessor would expect to see for this control.
- —Documented override and escalation procedure including reason code taxonomy and escalation thresholds
- —Override log records showing original AI output, reason code, reviewer correction, reviewer ID, and timestamp
- —Aggregate override statistics reports presented to AI Governance Committee on a defined cadence
- —Escalation records for overrides meeting threshold criteria, including resolution and any regulatory notification
- —Retention compliance evidence confirming override records are maintained for the required period
Implementation Notes
Key steps
- Require a reason code for every override — even a short taxonomy (factual error / policy conflict / missing context / other) produces valuable signal.
- Define escalation thresholds: which override types require senior review, legal review, or regulatory notification?
- Store overrides with the original AI output so future audits can assess decision quality in context.
- Publish aggregate override statistics to the AI governance committee quarterly.
Example Implementation
Healthcare provider using AI for clinical documentation assistance
Override Procedure — Clinical Documentation Assistant
Step 1: Reviewer selects "Override AI Output" in the workflow UI
Step 2: System requires selection of a reason code before proceeding:
FACTUAL_ERROR— AI output contradicts the clinical recordPOLICY_CONFLICT— output violates documentation policyMISSING_CONTEXT— AI lacked access to relevant informationCLINICAL_JUDGMENT— reviewer's expert assessment differsOTHER— free-text explanation required
Step 3: Reviewer enters corrected output; original and corrected versions stored together
Escalation thresholds:
- 3+ FACTUAL_ERROR overrides on the same patient in one session → notify Chief Medical Informatics Officer
- Any override flagging a potential patient safety concern → mandatory incident report (IRC-001)
Retention: Override records (original output, reason code, correction, reviewer ID, timestamp) retained 7 years
Control Details
- Control ID
- HOC-006
- Domain
- Human Oversight
- Typical owner
- AI Governance Team / Compliance
- Implementation effort
- Low effort
- Agent-relevant
- Yes