Journal of Engineering, Project, and Production Management, 2026, 16(8), 2026-0185
Perceived Artificial Intelligence Skill Demand Across the Construction Project Lifecycle: Evidence from the Rwandan Construction Industry
1 Department
Head, University of Rwanda College of Science and Technology, E-mail:
o.dosumu@ur.ac.rw (corresponding author).
2 Researcher, Information Systems
Department, University of Rwanda College of Science and Technology,
E-mail: musanasechristine@gmail.com
3 Construction Professional,
Department of Construction Economics and Management, University of
Rwanda College of Science and Technology, E-mail: tumusiimeryan11@gmail.com
4 Quantity Surveyor, Department of
Construction Economics and Management, University of Rwanda College of
Science and Technology, E-mail: ahishadonne2002@gmail.com
5 Student, Department of
Construction Economics and Management, University of Rwanda College of
Science and Technology, E-mail: ericaca2021@gmail.com
Project Management
Received August 10, 2026; revised September 9, 2026, September 13, 2026; accepted September 15, 2026
Available online October 20, 2026
Abstract: Artificial Intelligence (AI) is increasingly transforming construction processes, yet limited empirical evidence exists on the skills required by professionals across different stages of the construction project lifecycle, particularly in developing economies. This study evaluates the perceived demand for AI skills across the eight stages of the Royal Institute of British Architects (RIBA) Plan of Work in the Rwandan construction industry. A quantitative cross-sectional survey was conducted among 174 construction professionals representing architecture, engineering, quantity surveying and construction management. Data were collected using a structured questionnaire measuring the perceived demand for AI-related skills across the eight lifecycle stages. Descriptive statistics were used to assess and rank skill demand, while the Kruskal-Wallis H test examined differences among professional groups, and the Friedman test assessed differences across lifecycle stages. The findings show moderate-to-high demand for AI skills across all lifecycle stages. The use stage recorded the highest overall demand, followed by strategic definition, and manufacturing and construction, while handover recorded the lowest. Significant differences across lifecycle stages were identified using the Friedman test (χ² = 19.162, p = 0.008), although the practical effect was very weak (Kendall's W = 0.016), indicating modest variation in relative intensity. Most individual skills did not differ significantly across professional groups, suggesting a substantial common set of AI competencies alongside selected discipline-specific requirements. The study’s findings provide evidence for the development of targeted, stage-specific construction education, professional development and workforce strategies in Rwanda and comparable developing economies.
Keywords: Artificial intelligence; AI skills; construction industry; construction project; project lifecycle; Rwanda.
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Citation: Dosumu, O. S., Musanase, C., Kaganga, R. T., Ahishakiye, D., and Iradukunda, E. (2026). Perceived Artificial Intelligence Skill Demand Across the Construction Project Lifecycle: Evidence from the Rwandan Construction Industry. Journal of Engineering, Project, and Production Management, 16(8), 2026-0185.
