Journal of Information Technology in Construction
Journal of Information Technology in Construction
ITcon Vol. 31, pg. 699-737, http://www.itcon.org/2026/31
Application of artificial intelligence in construction health and safety management: A systematic review and path forward
| DOI: | 10.36680/j.itcon.2026.031 | |
| submitted: | October 2025 | |
| published: | June 2026 | |
| editor(s): | Kumar B | |
| authors: | Prosper Gbiengu*
Safety Innovation Integration Research (SIIR) Lab, Department of Construction Science, Texas A&M University, 574 Ross St, College Station, TX 77840, United States https://orcid.org/0000-0002-1909-2609 pgbiengu@tamu.edu Muhammad Khan, Ph.D Department of Built Environment, College of Science and Technology, North Carolina A&T State University 112-A Price Hall, 1601 East Market Street, Greensboro, NC 27411, United States, https://orcid.org/0000-0002-0838-9087 muhammadkhan607@gmail.com Abdullahi Ibrahim, Ph.D Safety Innovation Integration Research (SIIR) Lab, Department of Construction Science, Texas A&M University, 574 Ross St, College Station, TX 77840, United States https://orcid.org/0000-0003-2373-3269 aaibrahim@tamu.edu Sharjeel Anjum, Safety Innovation Integration Research (SIIR) Lab, Department of Construction Science, Texas A&M University, 574 Ross St, College Station, TX 77840, United States https://orcid.org/0000-0003-0678-7994 muhammadanjum@tamu.edu Md Nazmus Sakib, Ph.D Intelligent Systems and Emerging Technologies (iSET) Lab, Department of Civil Engineering, University of Texas at Arlington, Arlington, TX 76019, United States http://orcid.org/https://0000-0003-0390-792X mdnazmus.sakib@uta.edu Chukwuma Nnaji, Ph.D Safety Innovation Integration Research (SIIR) Lab, Department of Construction Science, Texas A&M Universi-ty, 574 Ross St, College Station, TX 77840, United States https://orcid.org/0000-0002-3725-4376 cnnaji@tamu.edu | |
| summary: | Effective worker health and safety (H&S) management remains a major concern in the construction industry. Traditional safety measurement methods, while valuable, fall short of achieving zero injuries in dynamic and complex work settings. In response to this limitation, researchers have turned to emerging techniques, such as artificial intelligence (AI), to enhance the efficiency of H&S management methods and develop predictive models for on-site mitigation of occupational hazards. Despite numerous studies showcasing potential benefits and limitations of AI in various construction H&S applications, a comprehensive synthesis tailored to construction workers' H&S management is needed. This study conducts a bibliometric and systematic literature review of various AI strategies (specifically machine learning and deep learning) for ensuring effective H&S management and identifies gaps in existing research. Leveraging a systematic review approach, 181 articles from relevant academic journals and conferences published up to July 2025 were analyzed. The findings suggest a rapid increase in AI-related H&S research, particularly in Asia and North America. Results revealed seven construction H&S management AI application themes: construction accidents, PPE detection, ergonomic risk, safety inspections, fatigue, safety behavior, and health and safety training. The study highlights the strengths and weaknesses of current applications and proposes areas for further investigation. This review offers foundational insights essential for developing robust prediction models and advancing the use of safe and ethical AI in construction H&S management. | |
| keywords: | construction, artificial intelligence, health management, safety management | |
| full text: | (PDF file, 1.173 MB) | |
| citation: | Gbiengu, P., Khan, M., Ibrahim, A., Anjum, S., Sakib, M. N., & Nnaji, C. (2026). Application of artificial intelligence in construction health and safety management: A systematic review and path forward. Journal of Information Technology in Construction (ITcon), 31, 699-737. https://doi.org/10.36680/j.itcon.2026.031 | |
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