Decision assurance is the set of evidence and review practices used to show how an AI-influenced decision was made, who reviewed it, and who approved it. It focuses on traceability: can an organization reconstruct the rationale, inputs, human checks, and escalation path behind a decision?
In cyber security, this matters because AI can speed up approvals, triage alerts, rank risks, or recommend access changes. If those decisions are not documented, a bad recommendation can be acted on without meaningful oversight, making errors harder to detect and abuse harder to prove. Decision assurance supports audit trails, accountability, and incident response by preserving records that show whether a person actually exercised judgment. Defenders use it to verify control effectiveness; attackers may try to bypass or pollute it by hiding manipulations in workflows, logs, or review queues. Strong decision assurance makes AI-assisted processes more defensible, reviewable, and resistant to covert misuse.