Digital Twin, Not Digital Ideal: Using Reality Capture and AI to Improve Healthcare Asset Management

Digital twins are often discussed as the future of facility management, but too many still function as idealized design models rather than accurate representations of existing building conditions. For healthcare facilities, where reliability, resilience, and capital planning are mission-critical, the value of a digital twin depends on how well it captures what is actually happening in the building today.

This session will show how new technologies—including unmanned aerial systems, thermal imaging, LiDAR, laser scanning, photogrammetry, and AI-enabled distress detection—can turn static records into a dynamic, visual, and data-rich platform for asset management. By documenting current conditions, mapping deficiencies, tracking repairs, and linking building history to precise locations, digital twins can help facility teams make better decisions with greater speed, confidence, and consistency. Rather than relying solely on record drawings, institutional knowledge, or design-intent models, owners can use reality capture to build and maintain a more accurate understanding of the built environment. These tools support better capital planning, more targeted repairs, improved coordination across teams, and a clearer view of how conditions change over time.

Attendees will learn practical approaches for moving from a “digital ideal” to a true digital twin that reflects existing conditions and supports long-term asset performance. The presentation will focus on how healthcare facility teams can use emerging capture and analytics technologies to reduce uncertainty, prioritize investments, document maintenance history, and improve outcomes across the building lifecycle.