Build a Defensible AI Incident Response Framework

When an AI-related concern emerges, inconsistent intake and ad hoc escalation can leave evidence fragmented, responsibilities unclear, and broader risk patterns undetected.

This white paper provides a practical framework for capturing, investigating, escalating, and remediating AI incidents.

Learn how to connect AI governance with legal, privacy, security, compliance, product, and technical teams through a repeatable, auditable response process.

KEY TAKEAWAYS

• Identify the minimum information every AI incident intake should capture

• Decide whether your program will investigate harms only or include hazards and near misses

• Translate organizational harm standards into reusable assessment criteria

• Create severity levels that trigger consistent ownership, investigation, and escalation