Topic

Bias Audits

Bias audits are systematic evaluations of AI systems to identify and measure discriminatory patterns in model outputs, training data, or decision-making processes. They are critical for enterprises to demonstrate fairness compliance, mitigate legal liability, and ensure their AI systems do not perpetuate or amplify historical discrimination. Regular bias audits help organizations meet regulatory requirements under frameworks like the EU AI Act and provide evidence of responsible AI governance to stakeholders and regulators.

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ResearchEU2026-06-26

Board Oversight Gaps Exposed: Diligent's AI Governance Guide Maps Three Lines of Defense, Fairness Audits, and EU AI Act Alignment for Directors and Audit Leaders

Diligent has published a practitioner-focused guide titled 'AI Governance: A Guide for Boards, Risk and Audit Leaders' that outlines how organizations should structure board oversight of AI, apply a three-lines-of-defense model, conduct fairness and bias audits, and assess third-party AI risk. The guide explicitly maps recommendations to the EU AI Act, NIST AI RMF, and OECD AI Principles. It provides concrete steps for defining leadership accountability and establishing cross-functional AI ethics committees.

board oversight three lines of defense EU AI Act bias audits third-party AI risk