The \"Steel Sentinel,\" an AI-driven predictive maintenance system, has been recently implemented at the \"Ironclad Forge\" manufacturing plant. The system is designed to analyze sensor data from various machines and predict potential failures, recommending maintenance actions to prevent downtime. After a week of operation, the Steel Sentinel flags the main hydraulic press, \"Hercules,\" as requiring immediate shutdown and a complete overhaul of its hydraulic system, citing anomalies in pressure readings and vibration patterns. However, the plant\'s chief engineer, Anya Petrova, with 25 years of experience, reviews the data and finds no evidence of critical failure. The Hercules press has been operating within acceptable parameters, and the recommended overhaul would halt production for three days, costing the company a significant amount. Anya believes the AI is misinterpreting minor fluctuations as signs of imminent failure. According to ISO 42001 guidelines regarding risk management in AI systems, what should Anya and the Ironclad Forge management do *first* to address this situation, balancing the AI\'s recommendations with Anya\'s expert judgment and the potential for significant production disruption? The plant has a documented AI policy, but it does not explicitly address override procedures.