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Introduction This study examines user-reported perceptions of GeoAI tools in supporting urban resilience applications, particularly in disaster preparedness, climate adaptation, and sustainable development. It explores how Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), based on the Technology Acceptance Model (TAM), influence the adoption of GeoAI tools in professional practice. Methods A survey was conducted with 149 professionals from the fields of urban planning, geomatics, and artificial intelligence. The study evaluated three widely used GeoAI tools—ArcGIS Pro, CityEngine, and QGIS with AI plug-ins—focusing on their perceived effectiveness in real-world urban resilience scenarios. Statistical analysis was used to assess the influence of PU and PEOU on tool adoption. Results ArcGIS Pro was rated as the most effective tool, particularly in disaster preparedness and climate adaptation, with a mean score of 4.6 out of 5.0. CityEngine and QGIS with AI plug-ins also received positive evaluations but exhibited higher barriers to adoption. Key challenges identified include data quality (65%), integration issues (55%), cost (50%), and lack of training (45%). The findings indicate that both PU and PEOU significantly influence adoption, with Perceived Usefulness emerging as the strongest predictor. Discussion The results highlight the critical role of usability and perceived value in the adoption of GeoAI tools for urban resilience. Addressing barriers such as data integration, cost, and training is essential to enhance adoption rates. Improving these factors can support more effective implementation of GeoAI technologies, ultimately strengthening urban resilience planning and decision-making.
Alkherret et al. (2026) studied this question.