Integrating Internet of Things (IoT) devices with Artificial Intelligence (AI)-based data analytics transform governance models in smart cities, enabling real-time data-driven decision-making for enhanced urban management. This paper explores the role of IoT-enabled systems in collecting extensive data from urban infrastructure, including traffic, energy usage, waste management, and environmental monitoring. Leveraging AI, these systems analyze data to generate actionable insights, optimize resource allocation, and predict future urban challenges. The research identifies key applications, such as adaptive traffic control, efficient energy distribution, and predictive waste management, highlighting how these innovations lead to improved service delivery, reduced costs, and heightened quality of life for citizens. However, challenges such as data privacy concerns, the high cost of implementation, and the need for advanced infrastructure are also addressed. The study discusses future trends, emphasizing the potential for 5G integration and more sophisticated AI algorithms to advance smart city governance further.