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Nanoscale application of Artificial Intelligence (AI) holds a high transformational potential for further advancement of sustainable hybrid energy solutions. Quantum dots and perovskite crystals at the nanoscale have been shown to increase efficiency in solar cells. Better performance in battery and supercapacitors by nanostructured materials such as graphene and nanowires enhances energy storage from renewable sources. AI balances these innovations by optimizing hybrid energy systems, large datasets that help predict demand and manage storage for energy while, at the same time, enhancing the generation of power by renewables such as solar and wind. Such system advancements ensure reliable integration into a grid, and integration is important in maximizing the use of renewable energy. Nanotechnology and AI coexist to make it possible for smart grids and decentralized energy systems to become a reality. Since nanosensors are coupled with analytics powered by AI, monitoring, resilience, and efficiency in the distribution of energy are significantly improved. AI also sustains alternating renewal, fossil fuel, and storage-based use of energy; ensuring it is supplied without interference with the environment. Nanomaterials contribute to lighter, energy-efficient transportation and building stock, while AI optimizes energy usage in pursuing a carbon footprint decrease and fostering sustainability. Hence, nanotechnology incorporated into AI in hybrid energy systems is promising with regards to addressing global challenges raised by the need for energy besides advancement in clean energy resilience with climate change.