Asset-intensive organizations face growing pressure to improve performance while reducing costs and risks. In an era dominated by AI-driven messaging and technology hype, it’s easy to feel overwhelmed by promises of prescriptive maintenance and autonomous operations. The reality is that sustainable improvement starts with clarity, not chasing buzzwords. Organizations must first identify their business needs, assess gaps, and prioritize opportunities before selecting technology. A structured Asset Performance Management (APM) approach provides the essential framework to data management and asset performance, helping organizations contain risks and build a foundation for advanced capabilities. When AI initiatives are grounded in APM principles and aligned with clear business objectives, organizations can unlock measurable value: reducing downtime, optimizing maintenance spend, extending asset life, and improving safety and compliance. This session explores a practical roadmap for bridging the gap between aspirational vision and real-world outcomes, leveraging pragmatic use cases of AI applications, and ensuring technology serves business processes – not the other way around.