The future of the built environment is being shaped by artificial intelligence, and the 2027 ASHRAE Global TechCon North America is seeking innovative presentations that showcase real-world applications, emerging research, and lessons learned from deployment.
The upcoming Call for Presentations will invite contributions across six key tracks. Topics may range from AI-enabled decarbonization, resilience planning, and district-scale energy systems to intelligent residential technologies, occupant-centric IEQ solutions, predictive building operations, and business strategies that support investment, accountability, and organizational transformation.
Researchers, practitioners, building owners, technology providers, and policymakers are encouraged to share case studies, deployment experiences, innovative methodologies, and measurable outcomes that demonstrate how AI is transforming the design, operation, and management of buildings and communities worldwide.
Watch for the official Call for Presentations opening soon and join us in advancing the next generation of intelligent, resilient, and sustainable built environments.
Tracks include:
Climate Change and Resilience
This track explores how AI can support mitigation of and adaptation to climate change in the built environment at the portfolio level. Topics include AI-enabled decarbonization planning, climate risk assessment, load flexibility for climate and grid resilience, and preparation for extreme weather and other long-horizon disruptions. Contributions may address climate scenario analysis, predictive modeling for climate-adaptive operation, resilience planning, infrastructure vulnerability assessment, and strategies for maintaining service under changing environmental conditions. Case studies demonstrating improved resilience, emissions reduction, or climate risk management through deployed systems are strongly encouraged.
Residential Buildings
This track focuses on the application of AI in residential buildings, from single-family homes to multi-unit residential developments. Topics include intelligent thermostats, occupant behavior modeling, distributed sensing, and demand response. Particular emphasis is placed on scalability, affordability, and user acceptance in residential contexts. Submissions may address challenges such as sparse data environments, privacy considerations, and integration with consumer technologies. Field studies and pilot deployments demonstrating measurable impacts on comfort, energy use, or grid interaction are of interest.
Indoor Environmental Quality (IEQ)
This track examines the use of AI to monitor, predict, and optimize indoor environmental quality, including thermal comfort, air quality, lighting, and acoustics. Topics include sensor fusion, occupant-centric controls, health and wellness analytics, and adaptive comfort models. Contributions may explore trade-offs between IEQ and energy performance, as well as methods to personalize indoor environments. Real-world implementations, validation studies, and human-subject evaluations that demonstrate improved occupant outcomes are particularly encouraged.
International Best Practices and District Energy
This track examines international best practices and AI applications at the district, campus, and community scale, including district heating and cooling systems, thermal networks, microgrids, energy sharing networks, and other integrated multi-building energy infrastructure. Topics include system-level forecasting, coordination of distributed energy resources (DERs), network optimization, digital twins for district infrastructure, and lessons learned from policies, standards, market structures, and deployments across different regions. Contributions may explore interoperability across multiple assets, transferability of successful strategies between jurisdictions, and operational coordination across community-scale systems. Case studies showcasing implemented district-scale solutions, measured network-level outcomes, and internationally relevant practices are highly encouraged.
Energy Management
This track focuses on AI-driven approaches to building-level energy management during day-to-day operation. Topics include predictive control (e.g., model predictive control), fault detection and diagnostics (FDD), energy forecasting, anomaly detection, supervisory optimization, and continuous commissioning within individual buildings or portfolios of buildings. Contributions may address integration with existing BAS, deployment challenges, operator workflows, and lifecycle considerations for sustained performance. Emphasis will be placed on practical applications, including measured energy savings, persistence of performance, operational scalability, and lessons learned from transitioning AI models from pilots to production environments.
Portfolio Planning, Business Strategy, Finance, & Accountability
This track examines how AI-enabled building strategies intersect with portfolio planning, business strategy, finance, and organizational accountability. Topics include return on investment (ROI), asset valuation, performance disclosure requirements, investor confidence, and access to capital, as well as enterprise risk considerations related to grid reliability, resilience, and liability. Contributions may explore business cases for decarbonization, indoor environmental quality (IEQ), and resilience, along with approaches for stakeholder engagement, organizational change management, and strategic decision-making across real estate portfolios. Submissions addressing market drivers such as net-zero commitments, disclosure rules, and evolving standards, particularly where they influence investment priorities or accountability frameworks, are strongly encouraged.