The acceleration of urbanization presents unprecedented challenges in managing city resources sustainably. This paper proposes a novel framework utilizing Artificial Intelligence (AI) and the Internet of Things (IoT) to enhance resource efficiency in smart cities, thereby contributing to sustainability. The crux of the framework lies in an integrated AI-IoT system capable of real-time data analysis and decision-making for optimizing resource allocation and consumption. In particular, the study will focus on critical urban systems—energy, water, and waste management—where AI can predict demand patterns, and IoT can provide granular consumption data. Through machine learning algorithms, the framework will analyze diverse datasets, ranging from energy usage to traffic flows, to identify inefficiencies and recommend corrective actions. For instance, in energy management, AI could optimize the distribution of renewable energy resources, while IoT devices monitor energy consumption patterns across the cityscape. The implementation challenges, including data privacy, cybersecurity, and the digital divide, will be critically examined. The potential socio-economic and environmental impacts of the framework’s deployment will also be discussed, showcasing how technology can align with the Sustainable Development Goals (SDGs). This paper aims to contribute to the discourse on sustainable urban development, providing actionable insights for policymakers, urban planners, and technology developers. It underscores the synergy between AI and IoT as a driver for innovation in sustainability practices within urban centers.