Purpose This study aims to identify and analyze the key challenges organizations face in adopting Generative Artificial Intelligence (Gen-AI) as a strategic enabler for transitioning toward Supply Chain 5.0, a paradigm that emphasizes sustainability, resilience and human-centricity, and to develop a novel AI-ENABLE framework that provides a structured and actionable roadmap for facilitating the responsible integration of Gen-AI to achieve next-generation supply chains. Design/methodology/approach A systematic literature review was undertaken to identify the major challenges associated with Gen-AI adoption in the context of Supply Chain 5.0. Expert validation was conducted to ensure contextual relevance, after which the Neutrosophic Decision-Making Trial and Evaluation Laboratory (N-DEMATEL) technique was applied to prioritize the identified challenges and classify them into cause–and–effect categories. This hybrid approach enabled the study to address uncertainty and subjectivity in expert judgments while uncovering causal relationships between adoption challenges. Findings The results reveal that skill shortages, high investment costs and data privacy concerns are the most influential causal challenges restricting Gen-AI adoption. These, in turn, escalate side-effect challenges, such as resistance to change management, scalability issues and a lack of transparency. The findings not only highlight the interconnected nature of these challenges but also establish skill development and strategic investment as foundational enablers for adoption. To address them, the proposed AI-ENABLE framework provides organizations with a structured mechanism for workforce upskilling, phased implementation, ethical governance, process re-engineering and continuous innovation – thereby ensuring sustainable, resilient and human-centric adoption of Gen-AI. Originality/value While prior studies have predominantly focused on the technical advantages and potential applications of Gen-AI in supply chain management, little attention has been paid to the practical adoption challenges that hinder its transition toward Supply Chain 5.0. This study fills that gap by systematically identifying and prioritizing these challenges using N-DEMATEL and by proposing the AI-ENABLE framework, which uniquely integrates human-centric, ethical, technological and financial considerations. This study contributes to both theory and practice by enriching the knowledge base with a novel decision-support framework that guides managers and policymakers in navigating adoption complexities and unlocking the transformative potential of Gen-AI for Supply Chain 5.0.
Garg et al. (Mon,) studied this question.