Abstract: The construction sector is undergoing an unprecedented qualitative transformation, driven by the rapid advancement of artificial intelligence technologies that open new horizons for improving project management, particularly in the areas of planning and resource allocation. In this context, this research aims to evaluate the effectiveness of AI applications by identifying and analyzing the available opportunities, most notably enhancing operational efficiency, supporting decision-making, and optimizing resource utilization, while also identifying the main barriers hindering their adoption in the construction sector. To achieve the research objectives, a questionnaire was designed involving 204 industry experts from the construction and artificial intelligence sectors, and the data were analyzed using structural equation modeling (PLS-SEM). The results showed that the operational efficiency improvement group ranked first among AI opportunities with the highest composite weight of 0.380, followed by quality improvement with a weight of 0.372, and then risk and safety with a weight of 0.336. Regarding challenges, the technical group topped the list of barriers with a weight of 0.391, followed by the organizational group with a weight of 0.382, and then the ethical and social group with a weight of 0.351. These findings reflect the key priorities that should be focused on to maximize the benefits of AI and address the most impactful barriers in the context of planning and resource management in construction projects. Based on these results, the study provides practical guidance for managers and developers to strategically align AI adoption with core industry needs. Keywords: artificial intelligence, construction management, resource optimization, PLS-SEM, planning management. Title: Artificial Intelligence Applications in Construction Management: Challenges and Opportunities Author: Ahmed samir, Ali Shreef, Mohamed Badawy International Journal of Civil and Structural Engineering Research ISSN 2348-7607 (Online) Vol. 13, Issue 2, October 2025 - March 2026 Page No: 24-34 Research Publish Journals Website: www.researchpublish.com Published Date: 25-March-2026 DOI: https://doi.org/10.5281/zenodo.19224425 Paper Download Link (Source) https://www.researchpublish.com/papers/artificial-intelligence-applications-in-construction-management-challenges-and-opportunities
samir et al. (Wed,) studied this question.