King Fahd University of Petroleum and Minerals (KFUPM) currently relies on administrative judgment for urban planning, which may introduce human errors and overlook environmental and social factors. This study examines the potential of Artificial Intelligence (AI) in enhancing urban planning decisions, using Autodesk Forma to analyze solar exposure, wind behavior, and microclimate variations across proposed building sites. The research utilizes an AI-driven site evaluation framework to conduct multi-faceted environmental analyses, including highly predictive wind movement simulations. This approach generated quantifiable metrics essential for sustainable urban design optimization, demonstrating, for example, that one design option achieved 0% uncomfortable pedestrian wind conditions, a key measure of success unattainable through conventional evaluation methods. The findings highlight AI’s role in improving planning accuracy, reducing reliance on static datasets, and supporting data-driven decision-making. However, human expertise remains essential for interpreting AI-generated outputs, ensuring alignment with institutional goals, and validating results. Future research should explore integrating custom datasets for enhanced wind analysis, AI-driven site selection automation, and expert-driven refinements to planning strategies. This study underscores AI’s value in urban planning while emphasizing the need for a hybrid AI-human decision-making framework.