Topic

AI Incident Tracking

AI incident tracking refers to systems and processes for documenting, monitoring, and analyzing adverse events, failures, or unexpected behaviors in AI systems. This capability is critical for enterprise AI governance because it creates an auditable record of problems, enables pattern identification across deployments, and supports root cause analysis to prevent recurrence. Organizations use incident tracking to demonstrate due diligence to regulators, inform model retraining decisions, and continuously improve AI safety and performance.

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Corporate PolicyUS2026-05-05

AI Incidents Surged Over 32% in 2024, NACD Guidance Urges Boards to Adapt Oversight Frameworks

The National Association of Corporate Directors (NACD) has published 'Tuning Corporate Governance for AI Adoption' as part of its 2025 Governance Outlook series, providing boards with a framework to adapt existing oversight mechanisms for AI-related risks. The resource reports a 26% increase in AI incidents from 2022 to 2023 and a further rise of over 32% in 2024, underscoring the urgency of board-level action. It calls on boards to evaluate how AI reshapes enterprise risk profiles and to establish appropriate internal reporting structures.

board governance risk management corporate oversight accountability transparency AI incident tracking United States auditing enterprise compliance