Artificial Intelligence in Construction Project Management: A Systematic Literature Review of Cost, Time, and Safety Management

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Authors: Yingxin Gao, Maxwell Fordjour Antwi-Afari, Yuxiang Huang, Zhen‐Song Chen, Bilal Manzoor
Cited by: 7
References: 116

Abstract

Artificial intelligence (AI) has become the leading technology for digital transformation in various industries. However, the digitalization of construction project management (e.g., cost, time, and safety) in the context of AI technology implementation is still limited. Therefore, this paper aims to conduct a systematic literature review of AI technologies in construction project cost, time, and safety management, and identify mainstream application areas, cross-domain synthesis, challenges, research gaps, and future research directions. By adopting the PRISMA approach, a systematic literature review was conducted to retrieve 392 articles from the Scopus database. The results presented mainstream application areas of construction project cost (i.e., cost estimation, cost prediction, cost index forecasting, cost control, cost optimization), time (i.e., planning and scheduling, delay risk prediction, time optimization, cycle time prediction), and safety (i.e., workers’ safety monitoring, on-site safety monitoring, personal protective equipment (PPE) detection, safety report text analysis, fall risk monitoring, safety accident prediction, and safety hazard identification and risk assessment). Moreover, the cross-domain synthesis, challenges, and research gaps of AI technologies in construction project management were discussed. Based on these findings, this paper suggests future directions to extend research in this domain. This paper would contribute to the construction project management research domain by providing key application areas and useful research directions, thus promoting digital transformation in the sector.

Fields of Study & Subjects

Occupational Health and Safety Research BIM and Construction Integration Construction Project Management and Performance

Publication details

Journal / source
Buildings
Publisher
MDPI AG
Volume
16
Issue
5
Pages
1061–1061
Publication date
7 March 2026
Language
EN