Most “AI audits” today are not audits. They are checklists designed to reduce anxiety, not risk. They ask whether a human is in the loop, but not whether that human actually adds judgment. They document tools, but ignore decision boundaries. They focus on compliance artifacts, while real failures happen in handoffs, hidden assumptions, and silent automation drift. A real AI audit is uncomfortable. It questions why the system exists, where it should not be used, and what happens when incentives push humans to rubber-stamp outputs. It maps accountability to decisions, not to roles or job titles. If your audit makes everyone feel safe but changes nothing in how decisions are made, you didn’t audit AI. You audited organizational comfort.