Artificial Intelligence (AI) is rapidly emerging as both a catalyst and a constraint in the global energy transition. On the one hand, AI offers unprecedented efficiency gains—optimizing grid performance, forecasting renewable generation, and enabling real-time balancing. On the other, the computational demands of training and deploying large models are driving an unprecedented surge in energy consumption, threatening to undermine climate goals and exacerbate systemic vulnerabilities. This report examines six interrelated ethical and technical challenges at the heart of AI’s integration into energy systems: the energy paradox, algorithmic bias and energy justice, cybersecurity and privacy risks, accountability and trust in opaque systems, workforce transformation, and the need for a comprehensive governance framework. Drawing on current research and real-world cases, it highlights the risks of inequitable cost distribution, infrastructure instability, and social exclusion, while outlining strategic recommendations for policymakers, industry leaders, and civil society. The analysis concludes that the success of the AI-driven energy transition will not be measured solely by technological performance but by our ability to ensure that it delivers a future that is clean, resilient, and just.