Artificial intelligence is advancing across asset management, promising to automate work orders, predict asset failures, and optimise technician scheduling. However, taking AI from isolated pilots to scalable, enterprise-wide execution requires navigating complex trade-offs. Join this multi-perspective panel discussion as industry leaders examine the deployment of AI in asset management through four essential lenses: technical, operational, ethical, and governance. Panellists will address the critical line between automation and human oversight, evaluating how to ensure reliable data integration, prevent model drift, uphold worker trust, and maintain strict regulatory auditability in safety-critical environments.