As the global shift toward renewable energy accelerates, it is vital for governments, energy management organizations, and policymakers to thoroughly assess environmental impacts and continue collaborating to ensure the sustainable and efficient use of renewable resources. The integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms has provided new opportunities for energy operators to optimize the effective utilization of renewable resources like solar, wind, wave, and geothermal energy. Through advanced predictive analytics, AI enables energy organizations to better forecast energy demands and manage grid fluctuations. AI-driven solutions have enhanced energy efficiency, reduced power wastage, streamlined power distribution, and improved grid management, while also enabling agile operations through predictive maintenance and other strategic innovations. These advancements have helped energy companies achieve their Sustainable Development Goals (SDGs) and have offered guidance to policymakers in transforming practices and processes so as to align with these ambitious objectives. This chapter presents a conceptual analysis and deeper insights into AI-driven renewable energy management solutions for organizations belonging to the energy sector.