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Shivam Gupta, Sachin Modgil, Régis Meissonier, Yogesh Dwivedi
Artificial intelligence (AI) as a technology has the potential to interpret and evaluate alternatives where multi-dimensional data is involved in dynamic situations such as supply chain disruption. This study aims to explore the role of resilient information systems (RIS) in minimizing the risk magnitude in disruption situations in supply chain operations. The study is conducted in the qualitative mode through semi-structured interview schedule for professionals of supply chains. Thematic analysis has been used to create emerging categories. The findings of this work present critical gaps in current information systems and demonstrate how AI-oriented systems can facilitate the ecosystem of disrupted supply chains to save costs and drive efficiency on multiple parameters. The study also proposes a conceptual framework where organizational values and architectural components can be viewed jointly for quick and adequate business decisions in the complex and uncertain disruptions. The framework presents the relationships among AI, information systems and supply chain disruption. Installing appropriate AI-based data acquisition, processing and self-training capabilities along with information system infrastructure can help organizations lessen the impact of supply chain disruption while aligning the transportation network and ensuring geographically-suitable supply chains and cybersecurity. Finally, the implications for theory and practice with the limitations and scope for future research are described.