Artificial Intelligence in Architecture: History, Evolution, and Future Prospects

Abstract

Artificial Intelligence (AI) has brought significant transformations to the field of architecture, ranging from the digitalization of design processes to the application of machine learning and deep learning technologies in various aspects of design, construction, and building management. These technological advancements have not only changed the way architects work but have also created new opportunities for developing more efficient, adaptive, and sustainable built environments. This study aims to examine the evolution of AI in architecture, evaluate its implementation in contemporary architectural practice, and identify the challenges and future prospects of its development. The research employs a literature review using a descriptive qualitative approach through the analysis and synthesis of various academic sources, scientific publications, and relevant case studies. The findings indicate that AI has evolved from Computer-Aided Design (CAD)-based drafting support into intelligent systems capable of facilitating design optimization, decision-making, smart building management, and the conservation of historic buildings. Various case studies demonstrate that AI contributes to improving design efficiency, structural optimization, building energy management, as well as the documentation and reconstruction of architectural heritage. Although AI offers considerable opportunities for realizing more innovative and sustainable architecture, its implementation still faces several challenges related to data quality, ethical concerns, the interpretation of creativity, and the readiness of the industry to adopt such technologies. The findings suggest that AI has substantial potential to become a strategic partner for architects in supporting the design process and the management of built environments that are more innovative, responsive, and oriented toward future needs.