Oyenubi, A. and Oyeyipo, O. O. (2026) Overcoming GenAI adoption barriers in construction cost management: Evidence from Nigeria. Construction Innovation, pp. 1-26. ISSN 1471-4175
Abstract
Purpose – Generative artificial intelligence (GenAI) holds significant potential to improve accuracy, reduce uncertainties and support proactive financial decision-making throughout the project lifecycle. Despite these promising capabilities, the adoption of generative AI in construction cost management remains limited and uneven. This study, therefore, aims to examine the barriers to adopting GenAI for cost management in the Nigerian construction industry and to propose viable strategies to overcome them. Design/methodology/approach – A quantitative research approach was adopted, with data collected through structured, closed-ended questionnaires administered to construction professionals. The data were analysed using both descriptive and inferential statistical techniques. Findings – The study identified nine critical barriers to the adoption of GenAI for cost management in the Nigerian construction industry. Exploratory factor analysis grouped these barriers into two principal components: internal organisational constraints and external risk and environmental uncertainty factors. The results highlight that GenAI adoption is a socio-technical process influenced by both organisational readiness and external conditions. In addition, the study provides practical value by developing a structured matrix that aligns each barrier with targeted strategies across technology, people, process and risk management dimensions, offering actionable guidance for improving adoption. Originality/value – This study contributes to digital transformation in construction by providing empirical, context-specific evidence on the adoption of GenAI for cost management in the Nigerian construction industry. It identifies and categorises nine critical barriers into internal organisational constraints and external risk and environmental uncertainty factors. The study further develops a structured matrix that links these barriers to targeted strategies across the technology, people, process and risk management dimensions. In addition, it extends the technology acceptance model by demonstrating how organisational and environmental factors influence GenAI adoption in a complex context.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | adoption; barriers; commercial management; cost management; digitalisation; generative artificial intelligence |
| Index terms: | cost management, construction industry, project lifecycle, accuracy, socio-technical, exploratory factor analysis, construction cost, evidence, construction professional, strategy, questionnaire, transformation, technology acceptance model, decision-making, artificial intelligence, Nigeria, digitalization, quantitative research, environmental factor, environmental uncertainty, dimension, risk management, methodology |
| Subjects: | research methods, industry analysis, management, environmental science, statistical analysis, financial risk, business, Geography, evaluation and assessment methods, health monitoring assessment and metrics, digital technology, artificial intelligence, project completion, professional development, data analysis and analytics, accounting and finance, decision analysis, risk assessment, acoustic properties, financial and cost management, data collection methods |
| Topics: | Geographical Context, Cost Management, Health and Safety, Business Strategy, Digital Applications, Information Management, Risk Management, Engineering Principles, Project Management, Research Practice, Sustainability |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here