Scaling portfolio decarbonization with AI and building energy modelling
Tuesday, November 4, 2025 1:15 PM to 2:15 PM · 1 hr. (US/Pacific)
Information
Many organizations are taking action to reduce their carbon emissions. This session presents the actions taken by one company to accelerate the decarbonization of its large real estate portfolio.
The session will begin with context on the legislative, reputational, financial, and market drivers of decarbonization for real estate. The presenters will then provide an overview of different tools available for portfolio decarbonization, highlighting the tradeoffs between using conventional engineering approaches - such as energy audits and building physics models - compared with newer AI and machine learning analytics.
This session will include a case study of how Amazon is scaling decarbonization retrofits across its building portfolio using Carbon Signal - a platform leveraging the complementary benefits of AI with the accuracy of building energy models to provide information comparable to an energy audit in a matter of minutes. The presentation will utilize and share candid real-world examples from Amazon in its decarbonization journey thus far, and Amazon's next steps as it moves forward on its carbon commitments.
By the end of the session, participants will leave with a strong understanding of the importance of decarbonization in the real estate sector and be able to compare the different tools and approaches available for decarbonization of large building portfolios - including use of AI - by examining scalability, efficiency, and accuracy.
The session will begin with context on the legislative, reputational, financial, and market drivers of decarbonization for real estate. The presenters will then provide an overview of different tools available for portfolio decarbonization, highlighting the tradeoffs between using conventional engineering approaches - such as energy audits and building physics models - compared with newer AI and machine learning analytics.
This session will include a case study of how Amazon is scaling decarbonization retrofits across its building portfolio using Carbon Signal - a platform leveraging the complementary benefits of AI with the accuracy of building energy models to provide information comparable to an energy audit in a matter of minutes. The presentation will utilize and share candid real-world examples from Amazon in its decarbonization journey thus far, and Amazon's next steps as it moves forward on its carbon commitments.
By the end of the session, participants will leave with a strong understanding of the importance of decarbonization in the real estate sector and be able to compare the different tools and approaches available for decarbonization of large building portfolios - including use of AI - by examining scalability, efficiency, and accuracy.
Pass Type
Conference PassVolunteer PassStudent Pass
Location
151
Program
Practical AI Applications in the Built Environment Summit
Track
Practical AI Applications in the Built Environment Summit
Learning Level
Intermediate
Learning Objective 1
Identify the regulatory and market drivers of decarbonization in the built environment
Learning Objective 2
Describe the challenges with conventional methods in developing decarbonization strategies and provide an overview of how AI and machine learning approaches can scale decarbonization for large building portfolios
Learning Objective 3
Compare the tradeoffs between different tools and approaches to decarbonization, including AI, in terms of scalability, efficiency, and accuracy
Learning Objective 4
Understand possible next steps after using a decarbonization analytics platform
Continuing Education Credit Offered
AIA LU|HSWGBCI
