AI and Digital Transformation in the Renewable Energy Sector: A Strategic Framework for Sustainable Business Performance

Abstract

Purpose: The global shift towards clean energy necessitates robust business strategies to address challenges related to intermittent supply, operational inefficiencies, and evolving market conditions. This study fills a gap in strategic management literature by exploring the role of Artificial Intelligence (AI) and Digital Transformation (DT) in enhancing sustainable business performance within renewable energy enterprises. Design/Methodology/Approach: Utilizing the Resource-Based View (RBV) and Dynamic Capabilities Theory, this study conducts a qualitative conceptual synthesis and systematic analysis of recent literature (2018–2026) to formulate an integrated strategic management framework. Findings: The study presents the AI-Driven Digital Transformation for Sustainable Energy (ADT-SE) framework. This model demonstrates that the alignment of technological drivers—such as predictive analytics, IoT, smart grids, and block chain—with core organizational capabilities significantly enhances financial performance, operational efficiency, and environmental stewardship. Practical Implications: The study offers renewable energy executives and policy planners a practical roadmap for capital allocation, digital risk management, and the development of cross-functional capabilities. Originality/Value: This research connects technical AI applications with corporate sustainability strategies within the Commerce and Management domain.