Due to the impact of urban heat islands (UHIs) on local temperature, air quality, energy consumption, and public health, the issue is severe in the frame of sustainable urban development. This study presents an investigation into artificial intelligence’s (AI) potential for analyzing and mitigating the effects of UHIs, with actionable insight into sustainable city planning. AI models, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), using a wide variety of data ranging from satellite images, climate conditions, population density, and land cover classification, have localized UHI hotspots, analyzed various contributing factors, and simulated the efficiency of several mitigation strategies. The most critical correlations of UHI intensity with urban features-building density, vegetation cover, and material use are shown. The AI models effectively predict temperature fluctuations and quantify the effects mitigated by green infrastructure of green roofs and urban parks. These simulations support city planners in decision-making at a prioritization level by cooling potential and informing data-driven sustainable urban policies. This study shows AI’s potential in analyzing high-accuracy UHI and informing resilience strategies in urban areas. This paper describes how AI could improve the urban environment by underpinning sustainable urban planning and improving the quality of life of the urban population in the face of climatic changes. In contrast, most modern challenges related to data quality and computational demands are being addressed. The novelty here is provided through high-resolution UHI data analysis for data-driven sustainable urban policy. The results identify significant correlations of UHI intensity with features such as building density, vegetation cover, and material use. That showed the capability of AI to predict the fluctuation of temperature and to quantify the cooling effect from green infrastructure. It provides evidence-based recommendations for urban planners, focusing on AI-driven insights that will enhance urban resilience and improve the quality of life in the face of climate change.