BUILDING INFORMATION MODELING (BIM) AND AI-DRIVEN RISK MANAGEMENT IN PAKISTAN’S CONSTRUCTION INDUSTRY

Abstract

This study investigates the impact of Building Information Modeling (BIM) adoption and AI-driven risk management on construction project performance in Pakistan’s construction industry. The construction sector in developing economies continues to face persistent challenges, including cost overruns, schedule delays, safety risks, and inefficient risk management practices. In response to these challenges, digital technologies such as BIM and Artificial Intelligence (AI) have emerged as transformative tools capable of enhancing project coordination, predictive risk analysis, and decision-making efficiency. A quantitative, cross-sectional research design was employed, and data were collected from 400 construction professionals, including project managers, engineers, consultants, and contractors. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine relationships among BIM adoption, AI-driven risk management, risk mitigation effectiveness, and construction project performance. The results revealed that BIM adoption significantly improves AI-driven risk management integration and directly enhances construction project performance. AI-driven risk management was also found to have a significant positive effect on risk mitigation effectiveness and project performance. Moreover, mediation analysis confirmed that AI-driven risk management plays a crucial role in transmitting the effect of BIM adoption on construction project outcomes, indicating a strong indirect pathway. The study concludes that the integration of BIM and AI technologies is essential for improving efficiency, reducing uncertainty, and enhancing overall project performance in Pakistan’s construction sector. Strengthening digital infrastructure, workforce competencies, and policy support is critical for accelerating the adoption of Construction 4.0 technologies.