Transformative integration of Artificial Intelligence in architectural design

The introduction of Artificial Intelligence (AI) into architectural design is transforming traditional practices. This paper presents the typological applications of AI in architecture, focusing on its contributions to conceptual design, performance optimization, and sustainability, highlighting its transformative impact on workflows in the Architecture, Engineering, and Construction (AEC) sector. The aim of the authors of the paper was to categorize and analyse the hierarchical applications of AI in architectural design. The primary objective – to evaluate AI’s roles in fostering creativity, enhancing efficiency, and supporting sustainable practices. Methodologically, the research incorporates a comprehensive review of typological classifications, experimental validations, and case study analyses. By synthesizing findings from recent literature and real-world implementations, the paper assesses both the potentials and limitations of AI across various stages of architectural design. The results of the study indicate a typological hierarchy of AI applications in architectural design, revealing its multifaceted contributions. In conceptual design, AI-driven generative tools empower architects to explore vast design spaces, enabling the creation of innovative and diverse solutions. In performance optimization, AI demonstrates significant efficiency gains by reducing design iteration times, minimizing material waste, and enhancing energy efficiency through advanced simulations. For sustainability, AI’s predictive analytics facilitate informed decisions on material selection and compliance with environmental standards, supporting the achievement of green building certifications. However, these advancements come with challenges, including a dependency on high-quality data, ethical concerns regarding decision accountability, and the demand for specialized expertise. Based on the results, it can be concluded that AI enhances creativity, precision, and sustainability in architecture, but its successful integration requires a collaborative human-AI approach, supported by robust ethical frameworks and ongoing skill development.