Schneider Electric Presents: Built to Learn: AI for Continuous Building Performance
Thursday, October 22, 2026 10:30 AM to 11:30 AM · 1 hr. (US/Eastern)
Sponsored Session
Information
"Buildings generate unprecedented volumes of operational data, yet much of that information remains locked within disconnected systems, limiting the ability of organizations to accelerate decarbonization and improve performance at scale. As owners, designers, and operators face increasing pressure to reduce emissions, improve efficiency, and demonstrate measurable outcomes, artificial intelligence is emerging as a powerful tool for transforming fragmented building data into coordinated action.
Join leaders from Schneider Electric, Arup, and Macquarie Asset Management for a cross-sector discussion on how AI-enabled analytics, digital platforms, and integrated data strategies are reshaping the built environment. Through real-world examples and portfolio-level insights, panelists will explore how organizations are connecting building systems, uncovering operational inefficiencies, and scaling performance improvements across diverse real estate assets.
The session will examine how data-driven decision making supports building optimization, informs capital planning, and advances decarbonization objectives throughout the asset lifecycle. Participants will gain practical insights into the role of AI in identifying opportunities for energy and carbon reduction, strengthening collaboration among stakeholders, and supporting performance outcomes aligned with LEED and other sustainability frameworks. Attendees will leave with a clearer understanding of how connected technologies can help translate building data into measurable business, operational, and environmental value."
Join leaders from Schneider Electric, Arup, and Macquarie Asset Management for a cross-sector discussion on how AI-enabled analytics, digital platforms, and integrated data strategies are reshaping the built environment. Through real-world examples and portfolio-level insights, panelists will explore how organizations are connecting building systems, uncovering operational inefficiencies, and scaling performance improvements across diverse real estate assets.
The session will examine how data-driven decision making supports building optimization, informs capital planning, and advances decarbonization objectives throughout the asset lifecycle. Participants will gain practical insights into the role of AI in identifying opportunities for energy and carbon reduction, strengthening collaboration among stakeholders, and supporting performance outcomes aligned with LEED and other sustainability frameworks. Attendees will leave with a clearer understanding of how connected technologies can help translate building data into measurable business, operational, and environmental value."
Continuing Education Credit
GBCI
Program
Sponsored Session
Pass Type
Conference PassConference Pass + Sustainable Finance & Investing ForumStudent PassSustainable Finance & Investing Forum 4 Day PassVolunteer Pass
Location
Room 402
Track
Sponsored Session
Learning Objective #1
Analyze how AI-enabled building platforms can aggregate and interpret data from traditionally siloed systems to support achievement and ongoing performance verification of LEED v5 energy, carbon, and operational performance credits.
Learning Objective #2
Evaluate how cross-functional collaboration among building owners, design teams, and technology providers can leverage data-driven insights to advance LEED's Integrative Process and improve credit-related outcomes throughout the building lifecycle.
Learning Objective #3
Assess how a portfolio-scale practice used AI and advanced analytics to identify decarbonization opportunities, optimize building performance, and support strategies aligned with LEED certification and recertification goals.
Learning Objective #4
Compare approaches for translating building data into actionable investment and operational decisions that improve efficiency, reduce emissions, and strengthen business cases for sustainable asset management.

