AI in sustainable urban development: a scientometric and thematic review supporting SDG 11

Artificial intelligence (AI) offers significant opportunities to reshape urban planning and governance. However, its integration with Sustainable Development Goal (SDG) 11 has yet to be fully examined. This study employs a scientometric analysis of 126 Q1-indexed articles published from 2019 to 2025, unveiling a notable increase in scholarly attention. The analysis shows that China, the United States, and the United Kingdom are the primary contributors, with the journal Sustainable Cities and Society leading in this research area. Mapping co-authorship networks, Simon Elias Bibri emerges as the most prolific and frequently cited researcher, serving as a central figure collaborating with Zaheer Allam and Ayyoob Sharifi. Keyword co-occurrences analysis produced four dominant clusters centred on Smart Cities, Deep Learning, Energy Efficiency, and Urban Planning, which closely align with the subsequent results of this research. The thematic analysis highlights ten principal domains where AI supports SDG 11, with Environmental Monitoring & Management and Urban Mobility & Traffic Management most prominent for enabling data-driven urban sustainability. The findings underscore that AI technologies, such as Machine Learning, Deep Learning, and Reinforcement Learning, enhance predictive capacity for optimizing resources and strengthening disaster resilience. However, their application faces systemic challenges such as fragmented data, high computational energy demands, and insufficient ethical frameworks to address algorithmic bias in public participation. A gap-spotting analysis reveals key research gaps in confusion, neglect, and application, especially in underrepresented socio-cultural contexts, unresolved sustainability concerns, and limited practical deployment. In practice, AI demonstrates promise for bridging implementation gaps by fostering participatory governance and adaptive infrastructure. These insights offer a policy pathway for integrating AI into urban decision-making, stressing that sustainable governance requires balancing technological advancement with ethical and environmental stewardship to realize lasting urban resilience.