This survey paper explores the application of artificial intelligence (AI) in optimizing power consumption across various sectors. It provides a comprehensive review of AI techniques used for power optimization, including machine learning, fuzzy logic control, reinforcement learning, genetic algorithms, swarm intelligence, neural networks, and predictive analytics. The paper highlights the importance of power optimization in reducing environmental impact, lowering operational costs, and ensuring a stable and sustainable energy supply. It discusses the integration of AI in power systems, such as smart grids, industrial automation, and thermal energy management, and emphasizes the role of intelligent systems in improving efficiency and sustainability. The paper also outlines the challenges and future directions in AI-driven power optimization, including the need for further research and development in this area. The study identifies key areas of AI application in power systems, such as photovoltaic systems, thermal energy management, smart grids, and industrial automation, and evaluates the performance of various AI techniques in these domains. The paper concludes that AI has the potential to significantly enhance power consumption optimization, contributing to more efficient and sustainable energy systems.This survey paper explores the application of artificial intelligence (AI) in optimizing power consumption across various sectors. It provides a comprehensive review of AI techniques used for power optimization, including machine learning, fuzzy logic control, reinforcement learning, genetic algorithms, swarm intelligence, neural networks, and predictive analytics. The paper highlights the importance of power optimization in reducing environmental impact, lowering operational costs, and ensuring a stable and sustainable energy supply. It discusses the integration of AI in power systems, such as smart grids, industrial automation, and thermal energy management, and emphasizes the role of intelligent systems in improving efficiency and sustainability. The paper also outlines the challenges and future directions in AI-driven power optimization, including the need for further research and development in this area. The study identifies key areas of AI application in power systems, such as photovoltaic systems, thermal energy management, smart grids, and industrial automation, and evaluates the performance of various AI techniques in these domains. The paper concludes that AI has the potential to significantly enhance power consumption optimization, contributing to more efficient and sustainable energy systems.