Global Journal of Engineering and Technology Research (GJETR) · Research article · Open access
From Measurement to Judgment: Identifying Ai-Resilient and Ai-Vulnerable Quantity Surveying Functions in Abuja, Nigeria
Femi Philip Olorundare, Abdulhammed Adebisi Sotomiwa, Rotimi Samuel Ayodele
4 September 2026 · Vol. 2, Issue 9, pp. 388-394
DOI: 10.65150/EP-gjetr/V2E9/2026-02
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What is this article about?
The study identifies the Abuja, Nigeria, quantity surveying functions vulnerable to AI and non-vulnerable to AI based on practitioners' perceptions, to assist in guiding upskilling and role adaptation. An electronic copy of a structured questionnaire was sent to a sample of practising quantity surveyors in Abuja.
Article at a glance
- Published
- 4 September 2026
- Volume / issue / pages
- Vol. 2, Issue 9, pp. 388-394
- ISSN
- 3051-3782 (online) · 3051-3774 (print)
- Licence
- CC BY 4.0 — free to read and reuse with attribution
- Peer review
- Double-blind, at least two independent reviewers
- Publisher
- EP Journals Group
Abstract
The study identifies the Abuja, Nigeria, quantity surveying functions vulnerable to AI and non-vulnerable to AI based on practitioners' perceptions, to assist in guiding upskilling and role adaptation. An electronic copy of a structured questionnaire was sent to a sample of practising quantity surveyors in Abuja. A total of 155 questionnaires were distributed and 101 valid questionnaires (65% response rate) were analysed in SPSS. The effect of AI on each of the functions, rated on a 5-point Likert scale, was measured on the basis of Mean Item Score (MIS) and Standard Deviation (SD), then analysed using Principal Component Analysis (PCA) with Varimax rotation. The highest impact was for cost estimation (MIS = 4.21), measurements and quantity take-off (MIS = 4.14) and professional development (MIS = 4.12), while the lowest were client consultation and advisory services (MIS = 3.65) and design coordination and collaboration (MIS = 3.70). PCA (KMO = 0.837; Bartlett's p < 0.001) resulted in the identification of four underlying dimensions explaining 63.34% of variance: strategic and commercial advisory roles, quality/compliance and professional development roles, core cost and measurement roles, and risk and cost control roles. The results showed that functions most impacted by AI cluster together around computational, data-intensive functions, while functions less impacted by AI cluster together around advisory, relational and judgment-based functions. Use of AI in cost estimation, measurement, and bill of quantities preparation should be emphasised, and professional bodies and universities need to update CPD and curricula to balance AI capability with human judgment.
Keywords: Artificial Intelligence, Professional Functions, Role Impact, Principal Component Analysis, Abuja
Cite this article
Femi Philip Olorundare, Abdulhammed Adebisi Sotomiwa, & Rotimi Samuel Ayodele (2026). From Measurement to Judgment: Identifying Ai-Resilient and Ai-Vulnerable Quantity Surveying Functions in Abuja, Nigeria. Global Journal of Engineering and Technology Research, 2(9), 388-394. https://doi.org/10.65150/EP-gjetr/V2E9/2026-02
@article{Femi2026,
title = {From Measurement to Judgment: Identifying Ai-Resilient and Ai-Vulnerable Quantity Surveying Functions in Abuja, Nigeria},
author = {Femi Philip Olorundare and Abdulhammed Adebisi Sotomiwa and Rotimi Samuel Ayodele},
journal = {Global Journal of Engineering and Technology Research},
year = {2026},
volume = {2},
number = {9},
pages = {388-394},
doi = {10.65150/EP-gjetr/V2E9/2026-02},
url = {https://doi.org/10.65150/EP-gjetr/V2E9/2026-02}
}Questions about this article
Who wrote this article?
Femi Philip Olorundare, Abdulhammed Adebisi Sotomiwa, Rotimi Samuel Ayodele.
Where and when was it published?
In Global Journal of Engineering and Technology Research, Volume 2, Issue 9, pages 388-394, published by EP Journals Group on 4 September 2026.
Is this article free to read?
Yes. It is open access under a Creative Commons Attribution 4.0 (CC BY 4.0) licence, so anyone can read, share and reuse it with attribution.
What is the DOI of this article?
10.65150/EP-gjetr/V2E9/2026-02 (https://doi.org/10.65150/EP-gjetr/V2E9/2026-02).
How do I cite this article?
APA: Femi Philip Olorundare, Abdulhammed Adebisi Sotomiwa, & Rotimi Samuel Ayodele (2026). From Measurement to Judgment: Identifying Ai-Resilient and Ai-Vulnerable Quantity Surveying Functions in Abuja, Nigeria. Global Journal of Engineering and Technology Research, 2(9), 388-394. https://doi.org/10.65150/EP-gjetr/V2E9/2026-02
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