Rapid urbanization has increased pressure on transportation, energy, water, waste, housing, and public service systems, creating urgent demand for infrastructure that is efficient, adaptive, and environmentally sustainable. This article examines the role of AI-driven smart infrastructure systems in supporting sustainable urban development. It focuses on how artificial intelligence improves infrastructure planning, monitoring, maintenance, and service delivery through data analytics, predictive modelling, automation, digital twins, and intelligent decision-support systems. The study adopts a narrative and conceptual approach by synthesizing literature on smart cities, urban infrastructure, artificial intelligence, and sustainability. The discussion shows that AI- enabled infrastructure can strengthen urban efficiency by optimizing traffic flow, energy consumption, water distribution, waste collection, building performance, and public governance. It also contributes to climate resilience through early warning systems, predictive maintenance, environmental monitoring, and improved emergency response. However, the successful adoption of AI-driven infrastructure depends on strong data governance, cybersecurity protection, ethical safeguards, technical capacity, public trust, and inclusive policy design. The article argues that AI should not be viewed only as a technological tool, but as a strategic component of sustainable urban transformation. A responsible and integrated framework is therefore required to ensure that smart infrastructure supports environmental protection, economic efficiency, social inclusion, and long-term urban resilience.
Zaka ud Din (2026) studied this question.