Incident Management

Incident Management establishes the processes for detecting, responding to, and reporting AI-related incidents and malfunctions. As AI systems are deployed in increasingly critical applications, organizations must be prepared to rapidly identify and address failures, and in many cases, report them to regulatory authorities within strict timeframes.

The EU AI Act introduces mandatory incident reporting requirements for high-risk AI systems. Article 73 requires providers to report any serious incident to market surveillance authorities without undue delay after becoming aware of it. Serious incidents include those presenting risks to health, safety, or fundamental rights, as well as those indicating infringement of obligations under the Act.

Effective incident management requires both technical capabilities (monitoring, alerting, diagnostics) and organizational processes (classification, escalation, remediation, reporting). Organizations must establish clear incident severity criteria, define response procedures for each severity level, and ensure appropriate personnel are trained to execute these procedures.

Post-incident analysis is equally important. Organizations should conduct root cause analysis to understand why incidents occurred and implement preventive measures to avoid recurrence. Lessons learned should feed back into risk management, testing, and monitoring processes.