The rapid urbanization of the 21st century has intensified the need for cities to become more resilient, efficient, and sustainable. Artificial Intelligence (AI) offers transformative potential in this context by enabling real-time data-driven decision-making, predictive modeling, and autonomous system control across diverse urban domains. This review explores the integration of AI technologies into smart city infrastructures with a focus on enhancing urban sustainability. It critically examines AI applications in energy-efficient building systems, intelligent transportation networks, air quality monitoring, waste management, and urban planning. Drawing from interdisciplinary literature and case studies, the review highlights how AI contributes to reducing emissions, optimizing resource allocation, and improving public services. While AI presents significant opportunities for systemic sustainability gains, the paper also underscores key challenges including data governance, algorithmic bias, energy consumption of AI systems, and the risk of technological exclusion. The findings emphasize the necessity of aligning AI deployment with inclusive governance models, ethical standards, and sustainable development goals. A strategic roadmap is proposed to guide future research and policy, emphasizing the importance of equitable data infrastructures, cross-sectoral partnerships, and transparent AI model design. This review contributes to a deeper understanding of how intelligent systems can be leveraged to address complex urban sustainability challenges in an era of environmental uncertainty.
Nwaigbo et al. (2025) studied this question.