AI Applications in Urban Planning explores how artificial intelligence techniques, machine learning algorithms, and data analytics transform city design, infrastructure management, and governance globally. This comprehensive resource examines how deep learning, optimization algorithms, and spatial analysis enable planners to improve transportation networks, optimize land use allocation, enhance housing accessibility, and manage resource consumption sustainably. Coverage addresses real-world AI applications across North America, Europe, Asia, and Africa including computer vision for urban monitoring, predictive modeling for population dynamics, and autonomous systems for infrastructure assessment. The book systematically covers forecasting methodologies, data integration from urban sensors, real-time traffic management, and resilience planning against climate hazards. Coverage includes challenges addressing algorithmic bias, data privacy protection, transparency, and equitable distribution of AI benefits across urban communities. Practical sections emphasize case studies demonstrating successful implementation and lessons from pilot projects. Readers develop competencies in spatial data analysis, algorithm selection, urban data interpretation, and responsible AI deployment. This volume serves urban planners, data scientists, policymakers, and administrators seeking comprehensive understanding of AI applications in contemporary urban planning.