Artificial Intelligence in Smart Urban Planning: Bibliometric Insights for Ghana’s Urban Future

Johannesburg, South Africa Mikenyarko1991@gmail.com Cities are growing at unprecedented rates, especially in developing countries, where unplanned urbanisation intensifies congestion, informal settlements, flooding risk, and service deficits. Ghana reflects these pressures, and conventional planning approaches are increasingly strained. Building on the global shift toward smart city governance, this bibliometric study examines the emerging intersection of Artificial Intelligence and urban planning, with specific relevance to Ghana’s urban future. The paper aims to map the intellectual structure of AI-enabled smart urban planning, identify dominant thematic clusters, and interpret collaboration patterns and practical pathways for a sustainable built environment in rapidly urbanising contexts. The study adopted a desk- based bibliometric design using the Scopus database, followed by structured screening to retain studies relevant to urban planning and the built environment. In total, 147 documents were included for analysis. Keyword co-occurrence and co-authorship mapping were conducted in VOSviewer to identify keyword clusters and collaboration networks. The results show four concise research clusters: AI-driven technologies and digital infrastructure for smart planning; machine learning for sustainable mobility and infrastructure optimisation; big data and remote sensing for sustainable development assessment and urban growth monitoring; and predictive analytics for data-driven urban development and participatory planning. The country collaboration map indicates a small but connected set of leading countries, the United States of America, China, and India, suggesting that knowledge production is concentrated and internationally networked. In practice, the findings imply that Ghana can improve planning transparency and resilience by strengthening data governance and interoperability, addressing institutional fragmentation, and piloting digital twin applications for flood risk analysis and infrastructure monitoring. Enablers of Artificial Intelligence for Sustainable and Disaster-Resilient Building Design in the Built Environment Innocent Chigozie Osuizugbo Depart