AI Governance Institute
Human Oversight
HOC · Human OversightHOC-006Low effortAgent-relevant

Override and Escalation Procedures

Added May 2026

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

1

Initial

Overrides happen informally with no documentation or escalation path.

2

Developing

Some teams log overrides informally; escalation paths are not consistently defined.

3

Defined

A documented procedure specifies how to override an AI decision, what to log, and when to escalate to a higher authority.

4

Managed

Override patterns are analyzed to identify systematic model errors or process failures.

5

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 record
  • POLICY_CONFLICT, output violates documentation policy
  • MISSING_CONTEXT, AI lacked access to relevant information
  • CLINICAL_JUDGMENT, reviewer's expert assessment differs
  • OTHER, 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
Typical owner
AI Governance Team / Compliance
Implementation effort
Low effort
Agent-relevant
Yes

Tags

overrideescalationhuman oversightaudit trail

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