In the realm of renewable energy projects, Artificial Intelligence (AI) and Machine Learning (ML) are employed to gather and analyze data to boost system efficiency. By leveraging AI techniques like regression, classification, and clustering algorithms, optimal operating conditions can be pinpointed to maximize energy extraction from wind and solar characteristics. These advancements result in increased efficiency and sustainability in renewable energy systems. Moreover, sophisticated deep learning models such as neural networks provide advanced capabilities for data analysis and improve operational control methods in energy conversion systems. Additionally, optimization algorithms like genetic algorithms and particle swarm optimization are instrumental in energy conversion processes. These algorithms aid in identifying optimal solutions for system configurations and control strategies to optimize energy efficiency. This chapter gives an overview on artificial intelligence techniques for energy conversion systems.