Developing a Green AI Governance Framework for Sustainable Digital Business Transformation

Abstract

Amid the rapid growth of Artificial Intelligence (AI) adoption in business environments, concerns regarding energy consumption, carbon emissions, ethical accountability, and sustainable governance have become increasingly significant, creating the need for frameworks that align AI deployment with sustainability objectives and digital transformation strategies. This study aims to develop a green AI governance framework that supports sustainable digital business transformation by integrating environmental, governance, and technological considerations into AI implementation practices. Using a Systematic Literature Review (SLR), relevant studies published between 2020 and 2025 were identified, screened, and analyzed to synthesize key themes, governance dimensions, and sustainability principles associated with green AI adoption in organizational contexts. The findings reveal that effective green AI governance is shaped by four interconnected dimensions including environmental sustainability, ethical and regulatory compliance, operational efficiency, and stakeholder accountability. Based on these findings, a conceptual framework is proposed that links AI lifecycle management, governance mechanisms, sustainability metrics, and business transformation outcomes to promote responsible and resource efficient AI deployment. The study concludes that organizations can enhance the sustainability and long term value of digital transformation initiatives by adopting a structured green AI governance approach that balances innovation, transparency, and environmental responsibility. The proposed framework contributes to both academic literature and managerial practice by offering strategic guidance for implementing sustainable AI systems while supporting organizational competitiveness and broader Sustainable Development Goals (SDGs).