How do you implement agentic AI for automated digital twin management?

Digital twin management agents maintain virtual representations of physical systems for simulation and monitoring. Configure agents with access to IoT sensor data, CAD models, simulation engines, and asset management databases. The agent keeps digital twins synchronized with physical counterparts by continuously ingesting sensor data and updating model states. Implement predictive simulations that forecast system behavior under different operating conditions. Detect discrepancies between digital twin predictions and actual system behavior that may indicate equipment issues. Support what-if scenario testing for operational changes before physical implementation. Generate system health reports comparing predicted versus actual performance. Track digital twin accuracy metrics and recalibrate models when prediction errors exceed thresholds. Support multi-scale digital twins from individual components to entire facilities.