Interdependencies Unveiled: MICMAC Analysis of BIM–AI Synergies in Construction

Abstract

The integration of building information modeling (BIM) and artificial intelligence (AI) holds transformative potential for the architecture, engineering, and construction (AEC) industry, enhancing project efficiency through innovative synergy factors. Despite growing recognition of individual synergy factors of BIM and AI in the AEC industry, no previous study has systematically examined the interdependencies and mutual reinforcement mechanisms among the full spectrum of BIM–AI synergy factors using a structural modeling approach such as MICMAC (a structural modeling technique that classifies variables by how much they drive versus depend on others in a system, helping identify true leverage points). Addressing this critical gap, this study examines systemic interactions among 15 primary advantage categories. Using the cross-impact matrix analysis (MICMAC) method, it analyzes data from 65 research papers and interviews with 16 digital technology experts in construction. Findings highlight Knowledge and Innovation Advancement and Sustainable Performance Optimization as pivotal variables driving improved outcomes, although the semi-unstable system state demands strategic management. The research reveals high-influence variables shaping efficiency and innovation, supported by impact chain analysis, offering a strategic framework for targeted investments. Despite limitations from limited large-scale project data, the study bridges gaps in understanding BIM–AI synergies, providing actionable insights for AEC stakeholders to optimize project delivery and sustainability. It recommends future research into detailed variable interactions and implementation challenges to enhance systemic stability. This pioneering framework guides professionals in leveraging BIM–AI integration to meet escalating project demands, fostering innovation and sustainable practices in the AEC sector.