Navigating the AI-powered transformation of renewable energy supply chains: A strategic roadmap to digitainability

Abstract

The global transition toward renewable energy necessitates supply chains that are not only sustainable but also digitally transformed - a concept we term digitainability. In this regard, Artificial Intelligence (AI) technology has emerged as a promising tool for advancing the digitainability of the renewable energy supply chain. This study investigates the transformative role of AI in advancing the digitainability of renewable energy supply chains. Through an extensive, content-focused literature review, the researchers identified 11 distinct AI functions critical to RESC digitainability. To better understand how these functions interact and complement each other, the study applied the Interpretive Structural Modeling (ISM) method, drawing on insights from supply chain experts. By employing ISM, we uncover the interdependencies among these functions and develop a strategic roadmap for their sequential implementation. Unlike prior studies, which often adopt linear approaches, this research provides a systemic and holistic framework for integrating AI capabilities to enhance supply chain sustainability. The roadmap equips managers and stakeholders with actionable insights to prioritize investments, foster collaboration, and navigate the complexities of AI adoption in RESC. By bridging theoretical exploration with practical application, this study contributes to the global effort to achieve a sustainable and digital energy future.