This session explores how assured, trustworthy use of AI for geospatial data can support decision-making and implementation strategies. The use of AI-enabled geospatial tools is increasing, spanning site suitability, climate resilience, risk management and investment decisions. Across all of these applications, questions of data provenance, model assurance, confidence levels and uncertainty analysis of the AI systems themselves become critical to responsible deployment.

We invite contributions on: methods for validating geospatial AI models and the datasets used; approaches to closing evidence gaps in data-poor areas; and frameworks to measure confidence and uncertainty in AI-derived geospatial outputs. We particularly welcome interdisciplinary contributions, including case studies that demonstrate how responsible GeoAI approaches can support fair access and devolution.