Abstract
Abstract: The field of architecture is undergoing a paradigm shift thanks to the integration of artificial intelligence (AI) into the design and planning processes. This has given architects new tools to analyze data, generate ideas, and predict the performance of buildings before they are implemented. This research aims to explore the role of AI in enhancing the quality of architectural decisions, improving environmental performance, and facilitating the realization of sustainable design solutions, particularly in regions with challenging climates. The methodology relies on the use of generative design software, such as Rhino/Grasshopper, Ladybug & Honeybee environmental analysis tools, as well as the application of optimization algorithms. Through which several design models are generated and analyzed environmentally (lighting, ventilation, energy consumption) to select the optimal model according to specific criteria. The approach was applied to a building design project (case study) in the hot and dry climate of Tripoli. The analysis begins with reading local climate data and then generating prototypes using generative design algorithms. The model was evaluated using environmental simulation tools, resulting in the selection of the most efficient design in terms of reducing heat load, enhancing natural lighting, improving ventilation, and lowering energy consumption compared to traditional models. The results showed that incorporating AI not only enhances environmental performance but also supports creativity and shortens design time