Cost management and artificial intelligence for architecture and urbanism

A systematic review

Abstract

The management process of architectural projects encompasses activities ranging from feasibility analysis in the early design stages to detailed cost assessments, including quantity takeoff and budgeting. In this context, artificial intelligence (AI) has emerged as a promising technology to optimize processes and enhance decision-making. This article presents the findings of a systematic literature review focused on the application of AI in cost management for architectural projects, with an emphasis on the architecture, engineering, construction, and operations (AECO) sectors. The review mapped the main thematic clusters and methodological approaches found in recent publications, identifying the most widely adopted AI technologies, such as machine learning, digital twins, and big data analytics. The results reveal that, while AI already contributes significantly to improving technical and operational efficiency, its direct integration into cost modeling and control is still in its early stages. Finally, the study discusses emerging trends and proposes directions for future research aimed at consolidating AI as a support tool for cost management in the field of architecture.