Home / Current Issue / Paper 1712537
BIM-AI Adoption in Philippine Public Sector Construction: A Study on Efficiency Gains and Implementation Challenges
Subject area: Science,Engineering and Technology · Area of research: Engineering Management
Abstract
This study investigates the Building Information Modelling (BIM) with Artificial Intelligence (AI) integration adoption in the Philippine public sector construction. It is also the aim of this study to determine the benefits that the government gain from integrating it and identify the challenges encountered by the operators. A survey questionnaire and semi-structured interview was utilized by this study to reveal the efficiency gained by the users in terms of cost, time, and quality. The data collected was also analyzed to identify the implementation challenges encountered. IBM SPSS Statistics 27.0.1 and NVivo software was used to analyze the data. Results showed that BIM-AI projects achieved cost reductions of 10% to 20%, while a reduction of 15% to 25% was attained in terms of time savings. In terms of quality, a substantial boost in BIM-AI projects was observed compared to traditional approach. Moreover, data collected showed that lack of training, lack of budget to buy subscriptions, and insufficiency of provided seminars were among the challenges encountered by the BIM-AI operators. Inadequate inter-agency coordination and the lack of standardized digital protocols hinder the scalable implementation of BIM-AI across government infrastructure projects.
Keywords
BIM, Building Information Modelling, AI, Artificial Intelligence, Philippine Construction Industry, DPWH, Efficiency Gains, Implementation Challenges
References
[1] Department of Public Works and Highways. (2021). BIM pilot projects and implementation strategies. DPWH Publications.
[2] Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2018). BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors (3rd ed.). Wiley.
[3] Lin, H., & Gao, Y. (2021). Integrating artificial intelligence into BIM for smart construction management. Automation in Construction, 124, 103553.https://doi.org/10.1016/j.autcon.2021.103553
[4] McKinsey & Company. (2021). The next normal in construction: How disruption is reshaping the world's largest ecosystem. https://www.mckinsey.com/industries/engineering-construction-and-building-materials/our-insights/the-next-normal-in-construction
[5] Reyes, M. A., & Santos, J. L. (2023). Challenges and opportunities in BIM adoption in Philippine public infrastructure. Philippine Journal of Construction Technology, 12(1), 45–60.
[6] Zhang, Y., Wang, X., & Liu, J. (2022). AI-driven BIM applications in public infrastructure. Automation in Construction, 136, 104205. https://doi.org/10.1016/j.autcon.2022.104205
[7] Vasantha Raju N., & Harinarayana, N.S. (2016, January). Online survey tools: A case study of Google Forms. Paper presented at the National Conference on "Scientific, Computational & Information Research Trends in Engineering, GSSS-IETW, Mysore.
[8] Santos, J. L. & Jocson, J. C. (2024). Adoption of Artificial Intelligence Technologies in the Philippine Construction Industry: A Review of Literature. Journal of Interdisciplinary Perspectives, 2(8), 461-471. https://doi.org/10.69569/jip.2024.0304
[9] Dimaculangan E. P. (2023). Issues and Challenges in the Philippine Construction Industry. Bitlis Eren University Journal of Science and Technology . https://dergipark.org.tr/en/download/article-file/3070730
[10] Marlon Mata, Rosein Ancheta, Gesselle Batucan, Gamaliel G. Gonzales (2023). Exploring technology acceptance model with system characteristics to investigate sustainable building information modeling adoption in the architecture, engineering, and construction industry: The case of the Philippines. Social Sciences & Humanities Open. Volume 10. 100967. ISSN 2590-2911. https://doi.org/10.1016/j.ssaho.2024.100967.
[11] Tran T.V. et al. (2024). A Review of Challenges and Opportunities in BIM Adoption for Construction Project Management. Engineering Journal. Volume 28: Issue 8. https://engj.org/index.php/ej/article/ view/4567/1348
[12] Khan, A. A., Bello, A. O., Arqam, M., & Ullah, F. (2024). Integrating Building Information Modelling and Artificial Intelligence in Construction Projects: A Review of Challenges and Mitigation Strategies. Technologies, 12(10), 185. https://doi.org/10.3390/technologies12100185
[13] Raqqad, zaid khalaf, The Integration of Bim and Ai in Modern Construction Projects: Between Theory, Applicability, and Realistically. Available at SSRN: https://ssrn.com/abstract=4703227 or http://dx.doi.org/10.2139/ssrn.4703227
How to cite this paper
@article{1712537,
author = {Kenneth L. Panahon, Noel T. Florencondia},
title = {BIM-AI Adoption in Philippine Public Sector Construction: A Study on Efficiency Gains and Implementation Challenges},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {426-431},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712537.pdf},
abstract = {This study investigates the Building Information Modelling (BIM) with Artificial Intelligence (AI) integration adoption in the Philippine public sector construction. It is also the aim of this study to determine the benefits that the government gain from integrating it and identify the challenges encountered by the operators. A survey questionnaire and semi-structured interview was utilized by this study to reveal the efficiency gained by the users in terms of cost, time, and quality. The data collected was also analyzed to identify the implementation challenges encountered. IBM SPSS Statistics 27.0.1 and NVivo software was used to analyze the data. Results showed that BIM-AI projects achieved cost reductions of 10% to 20%, while a reduction of 15% to 25% was attained in terms of time savings. In terms of quality, a substantial boost in BIM-AI projects was observed compared to traditional approach. Moreover, data collected showed that lack of training, lack of budget to buy subscriptions, and insufficiency of provided seminars were among the challenges encountered by the BIM-AI operators. Inadequate inter-agency coordination and the lack of standardized digital protocols hinder the scalable implementation of BIM-AI across government infrastructure projects.},
keywords = {BIM, Building Information Modelling, AI, Artificial Intelligence, Philippine Construction Industry, DPWH, Efficiency Gains, Implementation Challenges},
month = {December},
}