When a person overrides an AI-assisted accounts receivable finding, preserve both values and the reason for the change. A useful log records the source invoice, prior output, replacement decision, supporting evidence, reviewer, timestamp, and follow-up control. Keeping only the final value removes the information needed to review model behavior and human judgment.
NIST's AI Risk Management Framework Playbook calls for documenting human oversight, policy exceptions, escalations, and go or no-go decisions. NIST's generative AI profile also includes mechanisms for appeal, override, incident response, recovery, and change management. An invoice-level override log turns those broad governance ideas into a practical finance control.
Record the minimum useful override row
Capture:
- invoice and source-snapshot identifiers;
- finding or forecast field being changed;
- AI-assisted prior value and confidence or evidence label;
- human replacement value;
- reason code and a short explanation;
- source rows or approved documents reviewed;
- reviewer and decision time;
- whether the change affects amount, timing, priority, or ownership;
- next review date; and
- final disposition when the evidence is resolved.
Use the finance AI review record as the parent control. The override row should link to that record instead of becoming an unstructured note detached from the decision.
Separate source corrections from judgment overrides
Not every change is an override. If the invoice amount in the input was stale and a newer authorized export supplies the correct value, classify the event as a source update. If the source remains the same but a reviewer changes the predicted collection week, confidence label, exception type, or priority, classify it as a judgment override.
This distinction matters because the remedies differ. Source errors call for data-quality or mapping work. Judgment overrides may reveal a missing rule, ambiguous evidence, or a case that should remain under human review. The source-lineage guide helps keep both paths traceable.
Use bounded reason codes
A short controlled list makes patterns reviewable. Example codes include newer evidence, unsupported timing, wrong invoice linkage, policy boundary, duplicate finding, material context omitted, and reviewer correction. Allow a short explanation so the code does not flatten important context.
Do not use “human judgment” as the only reason. It says who changed the value but not why. Do not infer that the human decision is automatically correct; preserve later outcomes and reversals as separate evidence.
Route repeated overrides into controls
Review override patterns by field, source type, and reason. Repeated corrections to arithmetic, duplicate detection, or invoice linkage may belong in deterministic validation. Context-dependent timing or exception severity may remain a human decision. The deterministic-controls versus AI-judgment framework helps assign those boundaries.
Set an escalation rule for overrides that change a material amount, remove an exception, or move cash into the four-week range without new evidence. The exact threshold belongs to the finance team; the log should record the configured rule rather than invent one.
Decision rule
Never overwrite an AI-assisted AR decision without a trace. Preserve the prior value, replacement, evidence, reviewer, reason, and follow-up. AR Pulse intends findings to trace to supplied source rows and keeps human review in the loop; it does not guarantee model output or payment outcomes. Teams can apply for AR Pulse when a source-linked review process fits their receivables workflow.