The growing global energy demand and the pursuit of sustainability highlight the transformative potential of artificial intelligence (AI) and machine learning (ML) in energy systems. This thematic review explores their applications in energy generation, transmission, and consumption, emphasizing their role in optimizing renewable integration, enhancing operational efficiency, and enabling data-driven decision-making. By employing a thematic approach, this study categorizes and analyzes key challenges and opportunities, including economic considerations, technological advancements, and social implications. While AI/ML technologies offer significant benefits, their adoption in developing nations faces challenges, such as high upfront costs, skill shortages, and infrastructure limitations. Addressing these barriers through capacity building, international collaboration, and adaptive policies is critical to realizing the equitable and sustainable integration of AI/ML in energy systems.