Exam AAISM Topic 1 Question 101 Discussion

When an AI system experiences an attack after being in production for an extended period, the most effective mitigation strategy is to update the deployed training data with new adversarial data. This process strengthens the model's resilience by retraining it to recognize and resist attack vectors that were previously unknown or unaccounted for. According to the AI Security ManagementTM (AAISM) framework, risk mitigation for AI systems must address model robustness through adversarial retraining, data quality improvement, and model lifecycle hardening rather than relying solely on reactive measures.