The rapid growth of urban populations and the increasing demands of smart cities have led to a significant rise in waste generation, posing substantial environmental, economic, and social challenges. Traditional waste management practices are often inefficient, labor-intensive, and unsustainable, highlighting the need for innovative and technologically advanced solutions. Artificial intelligence (AI) has emerged as a promising technology to revolutionize waste management in smart cities, enabling the development of intelligent, efficient, and sustainable waste management systems. This chapter presents a comprehensive review of the current state of waste management in smart cities, highlighting the challenges and limitations of traditional approaches. We discuss the various types of waste generated in urban areas, including solid, hazardous, liquid, organic, and recyclable waste, and examine the environmental, economic, and social impacts of inadequate waste management. We then explore the potential of AI technologies, including computer vision, machine learning (ML), Internet of Things (IoT), and robotics, to transform waste management in smart cities. We examine how AI can be applied to optimize waste collection, sorting, recycling, and monitoring, reducing waste disposal costs, increasing recycling rates, and minimizing environmental harm. A novel intelligent system model is proposed, integrating multiple AI technologies to create a holistic waste management framework. This framework enables real-time monitoring and analysis of waste generation, composition, and disposal, facilitating data-driven decision-making and optimized resource allocation. The model also incorporates predictive analytics and machine learning algorithms to forecast waste generation patterns, identify areas of high waste concentration, and optimize waste collection routes. This research demonstrates the transformative potential of AI in addressing the complex challenges of urban waste management, contributing to the development of more resilient, sustainable, and livable cities. By synthesizing insights from scholarly databases, research papers, industry reports, and relevant publications, this chapter provides a roadmap for harnessing AI to create a more sustainable future for smart cities. Additionally, the chapter includes barriers to adoption and strategic solutions while also exploring future directions and research opportunities in AI-based waste management.