Artificial intelligence (AI) and its application in architecture design: a thematic review
The rapid advancement of AI technology has heightened interest in this field. It has broad implications across various industries, sparking extensive debates on AI’s potential, a concern particularly resonant within the architectural design industry. Despite the growing number of publications on AI...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universiti Putra Malaysia Press
2025
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/121063/ http://psasir.upm.edu.my/id/eprint/121063/1/121063.pdf |
| Summary: | The rapid advancement of AI technology has heightened interest in this field. It has broad implications across various industries, sparking extensive debates on AI’s potential, a concern particularly resonant within the architectural design industry. Despite the growing number of publications on AI and architectural design, comprehensive reviews are lacking in exploring its evolution, strategies, and future directions. Few researchers have conducted a thorough inventory of AI’s impact on architectural design or mapped current trends. Hence, this study specifically aimed to retrospectively analyze AI’s impact on architectural design and explore the evolving trends within AI-based architectural design using thematic review (TreZ) method. Data for this research encompassed a thematic review of 54 publications spanning from 2019 to 2023. The use of ATLAS. ti 23 aided in documenting and indicating the research directions pursued by scholars. The analysis identified six primary themes: 1) Architecture and Science, which includes research on complex systems, genetic algorithms, and machine learning;2) Architecture and Construction Management, including the development of frameworks that support decision making; architecture and interior design, which includes work on space-planning optimization and furniture and occupant arrangement;3) Architecture Interior Design; 4) Architecture and Urban; which encompasses attempts to develop tools to help design new cities; architectural engineering, where building performance analysis was the most-common AI application; 5) Architectural Engineering; and 6) Design Education and Training, in which AI appears most promising for advancing problem-based learning. The research indicates a growing emphasis on AI in architecture, aiming to improve algorithms, integrate with diverse tools like BIM, and enhance efficiency in design and engineering management to promote building sustainability. Future studies are expected to focus on refining algorithms and integrating AI more closely with architectural tools to boost efficiency and sustainability in building design and project management, in addition to organizational influences aimed at advancing building sustainability. |
|---|