Impact of intelligent building information modelling on new buildings and smart homes: Dubai and Sharjah

This research explores the digital paradigm shift toward Intelligent Building Information Modeling (IBIM) by developing and validating a structural model to assess its perceived impact across nine critical operational domains including user satisfaction, construction automation and sustainable design. Utilizing a quantitative methodology through Partial Least Squares Structural Equation Modeling (PLS-SEM), the study analyzes data from industry stakeholders in the United Arab Emirates (UAE), specifically focusing on the early-stage AI applications within the smart home ecosystems of Dubai and Sharjah. The findings empirically confirm that perceived IBIM effectiveness serves as a highly significant predictor of enhanced performance across all nine domains (p < 0.001). Notably, the model demonstrates its most potent predictive power in Decision-Making and Forecasting (R2 = 0.515), while simultaneously establishing a new ‘conceptual rule’ stating that predictive certainty is inversely proportional to operational complexity. By offering an exhaustive evaluation of nine dependent variables, this work provides one of the first multidimensional empirical validations of IBIM in the Middle East and presents a strategic roadmap for the global AEC industry to bridge the gap between theoretical AI potential and industrial reality.