Urbanization is a prevailing trend globally. More than 50% of the world’s population currently live in cities and the proportion is likely to grow to 70% by 2050 (World Bank Group, 2023). Amid this urbanization wave, smart cities have seen a noticeable rise since the 2010s (Almihat et al., 2022). Two other trends are picking up pace alongside the growth of smart cities. Firstly, there is greater focus on sustainable development since all United Nations (UN) member states adopted the seventeen global Sustainable Development Goals (SDGs) in 2015. Secondly, the advent of artificial intelligence (AI) transforms how people go about their daily lives and how cities function, including in pursuing the SDGs. Against this backdrop, there is value to study how AI could augment sustainability outcomes in smart cities. Specifically, this paper hypothesizes there are differences in how smart cities across regions apply AI to pursue sustainable development and seeks to uncover potential factors influencing such differences. The main methodology in this research is a set of comparative case studies involving three regions that have made notable progress in smart cities development – China, Singapore, and the United States. The findings from the comparative case studies validate the hypothesis that there are perceptible differences in how smart cities across regions deploy AI to pursue the SGDs. A potential factor for such differences could be regional sociocultural influences – an aspect that urban planners and policymakers should pay more attention to when applying AI in smart cities to improve sustainable development outcomes.
