Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector

The integration of artificial intelligence (AI) in the energy sector offers transformative potential but is hindered by a complex web of interconnected socio-technical challenges. The existing scholarship often addresses these issues in isolation, lacking a practical framework to guide stakeholders through the complexities of responsible deployment. This study addresses this gap by conducting a systematic literature review to develop and propose an integrative, actionable governance framework. The proposed framework is built on four core principles: Trustworthiness, Sustainability, Equity, and Collaborative Adaptation. Crucially, it operationalizes these principles through a four-phased implementation process, a stakeholder-specific action matrix with measurable key performance indicators, and a set of critical success factors. By synthesizing diverse solutions—from technical standards for data and security to governance mechanisms for ethical oversight and workforce transition—into a structured, lifecycle-based approach, this study argues that moving beyond piecemeal fixes is essential for mitigating systemic risks. This framework provides a testable roadmap for future research and a practical guide for policymakers and industry leaders seeking to harness AI’s full potential in a sustainable, ethical, and inclusive manner.