Impact of Artificial Intelligence on Resilient and Sustainable Supply Chain Management Post Covid-19

Abstract

The long-term viability of supply chains and additionally enhancing the resiliency to events like COVID-19 that can create unforeseen interruptions in the value SCs have become critical in the face of quickly shifting business conditions. Although sustaining a resilient supply chain network have historically been criticized for not having complete control over global supply networks, these issues are now more prevalent because of the unpredictable nature since COVID-19. With the help of artificial intelligence, this study seeks to uncover the difficulties in creating a robust and sustainable supply chain following COVID-19. This study’s background was provided by the automotive sector, one of the COVID-19-affected industries with a convoluted supply chain structure. According to the research, the biggest challenges faced by Sustainability Supply Chain Management (SSCM) before COVID-19 were tracing of supply chain, planning of demand, managing production, and planning of purchasing processes based on cause-and-effect categories. The three very crucial problems that must be solved following COVID-19 to guarantee sustainability and resilience of SCs must therefore address these identified challenges as well.