The combination of trade-policy shocks and COVID-19 disruption has exposed vulnerabilities that require rethinking for managing of global supply chain (SC). Businesses are forced to realign their global supply chains to maximize efficiency, and profits along with decisive actions on social and environment sustainable practices. The capability of Industry 4.0 AI for societal sustainable benefits and support for creating resilient supply chain is a matter of research importance. The dynamic paradigm shift and interconnections of resilient and sustainable practices for managing SC has not much been investigated in the literature and practitioners in emerging economies are still struggling for implementation. This paper attempts to integrate these two streams, identify issues faced by SC actors and develop conceptual framework for managing them. The study has two parts; the first literature review and interviews held with apparel SC stakeholders to identify complex supply chain issues post COVID-19. Later, soft system methodology (SSM) used to structure the research to understand resilient and sustainable issues in the system thinking, CATWOE analysis to identify root causes and design conceptual framework for the final implementation model from multiple functional domains expert perspectives. This paper proposes emerging Industry 4.0 technology framework including cloud-computing applications and artificial intelligence (AI) tools to manage key issues faced for building a resilient and sustainable supply chain in apparel sector. This research findings reveals the framework consisting of three main components criteria system, delivery system and Industry 4.0 AI- enabling system to manage sustainable practices and resilient performance challenges.