Artificial intelligence in the Nigerian construction industry: opportunities and challenges

Purpose Although artificial intelligence (AI) technologies are increasingly adopted worldwide, their diffusion in the Nigerian construction industry (NCI) remains limited. This study aims to investigate the transformative opportunities presented by AI and the critical challenges hindering its adoption in the NCI, framed by the technology acceptance model (TAM) and organisational change management theory (OCMT). Design/methodology/approach Using a quantitative approach within a positivist paradigm, data were collected via an electronic survey distributed through convenience sampling to professionals across government agencies, consulting firms and contractors. The data were analysed using descriptive and inferential statistics. Findings Results reveal AI’s potential to revolutionise operational efficiency and decision-making within the NCI. However, adoption is constrained by insufficient digital infrastructure and limited technical expertise. Addressing these barriers, particularly from the perspectives of individual acceptance (TAM) and organisational readiness (OCMT), is essential to fully harness AI’s transformative capabilities. Originality/value This study uniquely examines the socio-economic, technical and cultural factors shaping AI adoption in the NCI. By offering context-specific knowledge and strategic interventions, it informs policymakers, consultants and contractors of practical pathways for AI integration. The research contributes to the global discourse on AI in construction, especially in developing economies, providing a framework to foster innovation and sustainability in comparable contexts.

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Publication Details

Journal
Journal of Financial Management of Property and Construction
Published
2026-01-30
DOI
https://doi.org/10.1108/jfmpc-05-2024-0037
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence in the Nigerian construction industry: opportunities and challenges

Muhammad Aliyu Yamusa, Oluseyi Julius Adebowale, Emmanuel Onaivi Ajayi, Kahilu Kajimo-Shakantu et al.
Journal of Financial Management of Property and Construction
BIM and Construction Integration
article

Artificial intelligence in the Nigerian construction industry: opportunities and challenges

Muhammad Aliyu Yamusa, Oluseyi Julius Adebowale, Emmanuel Onaivi Ajayi, Kahilu Kajimo-Shakantu, Kabir Ibrahim
article en

Abstract

Purpose Although artificial intelligence (AI) technologies are increasingly adopted worldwide, their diffusion in the Nigerian construction industry (NCI) remains limited. This study aims to investigate the transformative opportunities presented by AI and the critical challenges hindering its adoption in the NCI, framed by the technology acceptance model (TAM) and organisational change management theory (OCMT). Design/methodology/approach Using a quantitative approach within a positivist paradigm, data were collected via an electronic survey distributed through convenience sampling to professionals across government agencies, consulting firms and contractors. The data were analysed using descriptive and inferential statistics. Findings Results reveal AI’s potential to revolutionise operational efficiency and decision-making within the NCI. However, adoption is constrained by insufficient digital infrastructure and limited technical expertise. Addressing these barriers, particularly from the perspectives of individual acceptance (TAM) and organisational readiness (OCMT), is essential to fully harness AI’s transformative capabilities. Originality/value This study uniquely examines the socio-economic, technical and cultural factors shaping AI adoption in the NCI. By offering context-specific knowledge and strategic interventions, it informs policymakers, consultants and contractors of practical pathways for AI integration. The research contributes to the global discourse on AI in construction, especially in developing economies, providing a framework to foster innovation and sustainability in comparable contexts.

Journal of Financial Management of Property and Construction
Ahmadu Bello University (NG), Tshwane University of Technology (ZA), Redeemer's University (NG), University of the Free State (ZA)
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
BIM and Construction Integration
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