The organization should define and document the event logging requirements for its AI systems across their lifecycle. This includes identifying the types of events to be logged (e.g., system actions, user interactions, errors, performance metrics) and the specific stages of the AI system's lifecycle where logging is required, such as development, testing, deployment, and operation.
Technical solutions should be implemented to ensure that these defined logs are effectively captured, especially during the AI system's operation. Logs should be securely stored, retained according to defined policies, and accessible for purposes such as auditing, incident investigation, performance monitoring, and compliance verification.