Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability

The fragmented nature of construction industry coupled with its complex and dynamic nature demands for innovative technologies to record better performance in project execution. In this respect, Artificial Intelligence (AI) based techniques posit a viable means to attain requisite efficiency in performance and alleviate the productivity of construction organizations. The adoption of sustainable practices in Construction Supply Chains (CSCs) lowers the environmental impact, lowers the risk of failure, and boosts competitiveness. The present study attempts to unearth potential issues in the adoption of AI practices in CSCs. Initially, the study identifies potential issues in the implementation of AI-based frameworks in CSCs by performing an extensive literature review and brainstorming sessions with industry experts. The exercise results in identifying 17 critical issues confronting the adoption of AI in CSCs which were subsequently subjected to fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) approach. The findings from the study reveal that "Lack of trust in AI outcomes", "Exploitation by hackers, cybercrimes and privacy intrusion", "Risk and cost associated with construction projects", "Uncertain processing and functions of AI algorithms", and "Unclear profits and advantages" were the top five influential causal issues that affect the adoption of AI in CSCs. This study is a novel attempt in the direction to identify and prioritize the potential issues in the adoption of AI-based frameworks in the Indian CSCs.