1Graduate School, University of la Salette Inc. Philippines
2Computer Engineering and Electronics Engineering Department, University of la Salette Inc. Philippines
3Civil Engineering Department, Quirino State University, Cabarroguis, Philippines
American Journal of Civil Engineering and Architecture.
2026,
Vol. 14 No. 3, 128-136
DOI: 10.12691/ajcea-14-3-6
Copyright © 2026 Science and Education PublishingCite this paper: Orlando D. Davin Jr., Genesis S. Jose, Wilfredo B. Baniqued. Evaluating the Use of Artificial Intelligence in the Field of Civil Engineering: Basis for a Proposed Comprehensive Professional Organizational Support Program.
American Journal of Civil Engineering and Architecture. 2026; 14(3):128-136. doi: 10.12691/ajcea-14-3-6.
Correspondence to: Orlando D. Davin Jr., Graduate School, University of la Salette Inc. Philippines. Email:
orlandojr.davin@qsu.edu.phAbstract
Artificial Intelligence (AI) is increasingly embedded in civil engineering work, yet empirical evidence on how practicing engineers actually use and experience AI remains limited, particularly in emergingeconomy settings [1]. This study examined AI utilization in civil engineering practice in Quirino Province, Philippines, and developed a comprehensive professional organizational support program based on the findings. A descriptivecomparative crosssectional survey was conducted among 150 practicing civil engineers using a structured 24item questionnaire covering four dimensions: technological, organizational, knowledge and skills, and ethical, cultural, and regulatory aspects. Descriptive statistics, independentsamples ttests, and oneway analysis of variance with post hoc testing were used to analyze the data. The overall mean score for AIrelated conditions was 2.89 on a fourpoint scale, indicating moderately favorable conditions. Knowledge and skills obtained the highest mean (3.03), followed by technological (2.96) and organizational aspects (2.88), while ethical, cultural, and regulatory aspects obtained the lowest mean (2.69), although they remained in the positive range. Significant differences were observed across demographic and sectoral groups, with younger engineers, those with 10 years or less of experience, and privatesector practitioners reporting more favorable AIrelated conditions than older, more experienced, and governmentsector counterparts; female respondents also perceived more favorable organizational support than male respondents. The findings indicate an emerging but not yet mature level of AI readiness in civil engineering practice and support the need for multidimensional interventions. A comprehensive professional organizational support program is proposed to strengthen AI adoption through capacitybuilding, stronger institutional backing, improved digital infrastructure, and clearer ethical and regulatory guidance, which may be useful for similar developingcountry contexts [2,3].
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