AI for Sustainable Cities: Bridging Innovation and Feasibility

AI for Sustainable Cities: Bridging Innovation and Feasibility

Wednesday, November 5, 2025 2:15 PM to 3:15 PM · 1 hr. (US/Pacific)
Technology and Innovation

Information

Artificial intelligence (AI) is rapidly advancing urban sustainability by transforming how cities monitor environmental conditions, plan infrastructure, and manage resources. This session brings together cross-sector experts to explore practical, real-world AI applications across a wide range of urban systems—air and water quality monitoring, extreme heat assessment, wastewater and stormwater infrastructure, energy demand forecasting, digital twins for asset management, and multimodal transportation analytics.


Each case will be examined through three integrated lenses: sustainability impact (e.g., emissions reduction, public health outcomes, resilience); implementation readiness (e.g., data availability, integration with existing systems, institutional capacity); and growth and adoption potential (e.g., scalability, replicability, alignment with funding or policy incentives). This framing provides attendees with a practical structure to evaluate AI applications based not only on technological promise but also on their applicability in varied local contexts.


The panel will also address real-world challenges that often limit or delay AI adoption. These include fragmented data systems, lack of interoperability, evolving ethical guidelines, algorithmic bias, unclear regulatory pathways, and limited technical capacity within local governments. Panelists will share specific examples of how they have navigated or overcome these barriers and offer strategies for advancing responsible, equitable AI deployment in urban environments.


Designed for practitioners, policymakers, and decision-makers, this session will help participants better understand where AI can realistically deliver impact today, and where groundwork is still needed, such as improving data governance, upgrading infrastructure, or strengthening policy alignment. Whether your focus is decarbonization, resilience, transportation, or public health, the session offers actionable insights and criteria to support strategic AI evaluation and implementation in your city or community.

Pass Type
Conference PassVolunteer PassStudent Pass
Location
402AB
Program
Greenbuild
Track
Data Driven Innovation
Learning Level
Intermediate
Learning Objective 1
Examine diverse real-world applications of AI in urban sustainability, including environmental monitoring, infrastructure management, mobility systems, and energy forecasting.
Learning Objective 2
Apply a structured lens—sustainability impact, implementation readiness, and growth/adoption potential—to evaluate AI technologies in the context of city and community development.
Learning Objective 3
Identify common barriers to AI adoption in the built environment, such as data limitations, policy gaps, interoperability issues, and ethical concerns.
Learning Objective 4
Explore practical approaches for responsible AI implementation, including data governance, capacity building, and policy alignment.
Continuing Education Credit Offered
AIA LU|HSWGBCI