According to the ISACA AAIA™ Study Guide, transparency is the cornerstone of AI auditing. For an auditor to rely on an AI-driven tool, the tool must provide " explainability " —the ability to describe how a specific conclusion or anomaly was identified. Without explainability, the AI remains a " black box, " preventing the auditor from exercising professional skepticism or justifying audit findings to stakeholders. While optimizing resources and supporting statistics are beneficial, they do not provide the necessary assurance that the model ' s logic is sound, unbiased, and compliant with regulatory standards. Auditors are required to validate the rationale behind automated decisions to ensure accountability.