Mapping the adoption of artificial intelligence in urban mobility

Urban transportation systems are undergoing a critical transformation driven by advances in artificial intelligence (AI). Despite many technical and theoretical discussions of AI technologies and a few case studies of AI implementation in selected cities, there remains a large gap in our knowledge about the landscape of the adoption of AI in urban mobility. This study addresses this gap by asking: where, when, how, and for which modes is AI being integrated into urban mobility across Europe? By systematically searching authoritative and publicly available data sources, i.e., the EU Urban Mobility Observatory and official city websites, complemented by manual content analysis, this work documents the geographic distribution, temporal trends, use cases, and transportation modes of AI adoption. As of the end of 2025, the analysis identified 107 AI deployments across 82 cities in 22 European countries. It shows a clear acceleration in adoption after 2022. The deployments fall into eight broad categories: infrastructure condition monitoring, traffic monitoring and analytics, vehicle automation, traffic signal control, public-facing digital services, parking management, transport service operations, and violation detection. In terms of transport mode, adoption is road-centric, with road applications accounting for 89% of recorded cases, while rail, air, waterborne, and cross-modal deployments are relatively rare. The compiled data are openly available online. This work is among the first efforts to establish an empirical base for assessing the prevalence of AI in urban mobility. It aims to provide urban planners, policymakers, and researchers with a better understanding of current AI adoption practices in the European context.