ARTIFICIAL INTELLIGENCE AND BUILDING INFORMATION MODELLING AS PREDICTORS OF EFFICIENT ARCHITECTURAL DESIGN AND CONSTRUCTION PROJECT DELIVERY IN NIGERIA

This study examined Artificial Intelligence (AI) and Building Information Modelling (BIM) as predictors of efficient architectural design and construction project delivery in Nigeria. The persistent problems of cost overrun, time overrun, design errors and project abandonment in the Nigerian construction industry provided the motivation for the investigation. Three objectives, research questions and hypotheses guided the study. A descriptive survey design was adopted, and a structured questionnaire was administered to a sample of 280 registered architects, builders, quantity surveyors and engineers drawn from architectural and construction firms in Lagos, Abuja and Enugu, of which 246 valid responses were retrieved. Data were analysed using performance percentage analysis, descriptive statistics (mean and standard deviation), Pearson Product Moment Correlation and simple linear regression at the 0.05 level of significance. Findings revealed that AI and BIM are perceived as highly effective predictors of design quality, cost-time performance and collaborative project delivery, with grand means above the 3.00 criterion. The correlation and regression analyses showed positive and statistically significant relationships between AI–BIM adoption and efficient project delivery (p < 0.05), with AI–BIM jointly explaining a substantial proportion of the variance in delivery efficiency. However, high software cost, shortage of skilled personnel, weak digital infrastructure and the absence of a national BIM mandate were identified as the dominant barriers to adoption. The study concluded that AI and BIM are significant predictors of efficient project delivery and recommended capacity building, government policy intervention and a phased national BIM mandate.