Route low-confidence AI outputs to an exception queue

Confidence can help triage, but a high-confidence invalid schema or critical action still needs review. The router should combine multiple acceptance rules.

Apply three gates

The automation lab evaluates four fixture outputs.

from automation_cases import exception_queue_case

result = exception_queue_case()
assert result["accepted"] == ["O1"]
assert result["review"] == ["O2", "O3", "O4"]
assert result["rows"][3]["confidence"] == 0.99
assert result["confidence_only"] is False

O4 is high confidence but critical, so it still routes to review. The scores are authored; no model ran.

Make the queue operational

Calibrate scores on representative labelled data and define thresholds by task slice. Add deterministic schema/business validation, unsupported-category detection, source support, novelty, policy flags and consequence. Log a stable reason for each route.

The queue needs priority, owner, service objective, source evidence and safe replay. Alert on age and volume. Reviewers must be able to accept, correct, reject or escalate; their action should never modify the original evidence silently.

Monitor auto-accept error, queue precision, review time and missed critical cases. Revisit thresholds when models, prompts or traffic change. Protect a random reviewed sample of accepted output so unknown failure types remain visible.

The Generative & Agentic AI course connects evaluation confidence to human oversight.

Exercise

Create twenty fixture outputs with score, schema and risk. Tune on development cases, lock the rule and report holdout auto-accept errors plus expected review capacity.

Continue learning

This article is part of the Business automation with AI sequence. Use the neighbouring tasks when you need the prerequisite or the next application.

• Review the prerequisite or neighbouring task in Automate a knowledge-base update proposal with review.
• Continue with Estimate an automation's operating cost from event volume.

Reference: NIST AI RMF Generative AI Profile.