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The ever-happening disruptive events interrupt the operationalisation of manufacturing organisations resulting in stalling the production flow and depleting societies with products. Advancements in cutting-edge technologies, viz. blockchain, artificial intelligence, virtual reality, digital twin, etc. have attracted the practitioners’ attention to overcome such saddled conditions. This study attempts to explore the role of artificial intelligence (AI) in building the resilience of production function at manufacturing organisations during a COVID-19 pandemic. In this regard, a decision support system comprising an integrated voting analytical hierarchy process (VAHP) and Bayesian network (BN) method is developed. Initially, through a comprehensive literature review, the critical success factors (CSFs) for implementing AI are determined. Further, using a multi-criteria decision-making (MCDM) based VAHP, CSFs are prioritised to …