The role of artificial intelligence in developing engineering project management

Authors

DOI:

https://doi.org/10.18488/76.v13i1.4751

Abstract

This study aims to verify the role of artificial intelligence in developing engineering project management. It seeks to determine the feasibility of implementing artificial intelligence to increase productivity, improve safety, reduce costs, and save time within engineering projects. The focus of the study is on two approaches to project management: traditional, which does not involve extensive integration of the latest intelligent systems, and innovative, where artificial intelligence is used for automated decision-making and risk forecasting. The methodological tools include pairwise comparison methods based on the Saati scale, as well as formulas for integral assessment, which compare the total benefits and opportunities with costs and risks. The results indicate that the innovative approach with deep integration of artificial intelligence has a higher overall indicator due to better productivity, more efficient resource allocation, and a more flexible security system, despite the additional initial costs and risks of implementation. In the long term, this approach allows for significant time savings and improved economic performance, which is critically important in the context of global competition and rapid technological change. This study confirms the feasibility of using artificial intelligence and provides an analytical tool for rational decision-making between traditional and innovative approaches to engineering project management.

Keywords:

Artificial intelligence, BOCR method, Costs, Engineering project management, Management decision-making, Optimal approach to management, Pairwise comparisons, Productivity, Risks modeling, Safety.

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Published

2026-02-02

How to Cite

Al-Bataineh, . . F. A., Al-Momani, T. A. K. ., Alrousan, M. A. ., AlJabali, A. M. A. ., & Jarah, B. A. F. . (2026). The role of artificial intelligence in developing engineering project management . Review of Computer Engineering Research, 13(1), 36–48. https://doi.org/10.18488/76.v13i1.4751