Topic

Audit

Audit refers to the systematic examination and evaluation of an organization's AI systems, processes, and controls to verify compliance with policies, regulations, and established standards. In AI governance, audits assess model performance, data handling practices, algorithmic bias, and decision-making transparency to identify risks and ensure accountability. Regular audits are essential for demonstrating due diligence to regulators, stakeholders, and customers while detecting issues before they escalate into compliance violations or operational failures.

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ResearchGlobal2026-06-02

Urban AI Governance Case Studies Reveal a Three-Part Control Stack That Enterprise Compliance Teams Are Still Building Separately

A CIDOB research report compiles comparative case studies of city-level AI governance programs across multiple jurisdictions, highlighting algorithm registers, lifecycle management approaches, mandatory high-risk system audits, and procurement conditions as foundational tools. The report's core finding is that these controls produce the most durable governance outcomes when integrated into a single stack rather than administered as isolated programs. Enterprise compliance teams can draw directly transferable lessons from municipal implementations that are, in several cases, more operationally mature than their private-sector counterparts.

algorithm register procurement governance AI lifecycle audit inventory