The report, produced in collaboration with the Data-Driven EnviroLab, acts as a practical guide to help city officials systematically navigate and evaluate the emerging landscape of Climate AI solutions. It introduces a multi-dimensional framework assessing tools across key dimensions like data requirements, technology readiness, and institutional capacity. Key findings show that while AI offers promising tools for urban climate action, the landscape is still maturing with over half of the cataloged solutions still in pilot or early adoption phases. It also underscores that a tool’s feasibility depends heavily on a city’s internal data quality and governance structures.

The Data-Driven EnviroLab (DDL) is an interdisciplinary research group that utilizes cutting-edge data analytics, remote sensing, and machine learning to evaluate environmental policies and track sustainability progress, with a particular focus on climate action at the city and subnational levels. The lab is directed by Dr. Angel Hsu, an Associate Professor of Environmental Studies and Public Policy at the University of North Carolina-Chapel Hill, whose pioneering research bridges the gap between data science and international climate governance.

Download the report here.

Check out the Dashboard here.