Potential domains, challenges and evaluation standards for integrating artificial intelligence and BIM into construction processes

Abstract

Purpose – This research examined the potential integration of artificial intelligence (AI) with building information modeling (BIM) in construction organizations, the main operational difficulties of integrating BIM and AI and the assessment criteria for integrated BIM–AI in construction companies. Design/methodology/approach – The study combined the strategic alignment model and balanced scorecard theoretical views to establish sub-constructs for the application domains, operational problems and assessment criteria of integrated BIM–AI. Findings – The study’s findings indicate the potential applications of BIM–AI, including an AI-supported BIM content recommender system, predictive AI models for defect identification and an AI-generated structural engineering BIM model. The operational hurdles to integrating BIM and AI include disparities between AI and BIM models, the loss of skilled personnel and motivation and excessive workloads. Originality/value – This study’s originality stems from its innovative approach to showcasing the effective use of AI in BIM for construction operations, as well as strategies for establishing smooth integration and interoperability between BIM and AI systems.