Cost per verified outcome is the total expense needed to produce one result that has been checked and is safe to ship. Unlike simple cost per task, it includes human review, rework, validation, false positives, and any correction loop needed to reach a trusted answer. In AI-enabled security work, that means counting the full operational cost of getting from raw model output to an approved alert, report, rule, or ticket.
This metric matters in cyber security because attackers often benefit when defenders optimize for speed or volume instead of assurance. A cheap model that creates many unverified alerts can raise noise and hide real threats, while a well-tuned workflow may cost more upfront but produce fewer, higher-quality outcomes. Security teams use this measure to compare detection pipelines, phishing triage, code review assistants, and malware analysis tools. The goal is not the lowest output cost, but the lowest cost for a result that survives verification and can be acted on with confidence.