This chapter delves into the critical role of artificial intelligence (AI) in the rapidly evolving field of robotics, examining how AI advancements enable robots to operate with greater autonomy, efficiency, and safety across diverse industries. The text is structured around three key pillars of robotics: perception, control, and planning. The chapter explores how AI, particularly machine learning, is revolutionizing robot perception by enhancing techniques like computer vision and sensor fusion, allowing robots to “see” and interpret their environments in a more nuanced manner. For robot control, it analyzes the impact of techniques like reinforcement learning (RL) and imitation learning (IL), which enable robots to execute actions with greater robustness and adaptability by learning complex control policies through experience and demonstration. In the realm of robot planning, the chapter details how AI-driven search, sampling, and learning-based methods enhance the generation of action sequences, allowing robots to strategize effectively in uncertain and dynamic environments. Furthermore, the chapter examines the emerging trend of end-to-end frameworks, which integrate perception, planning, and control into a single, unified system for more holistic learning and simplified development. Finally, it addresses the limitations and future directions across these areas, considering challenges such as data efficiency, safety, and generalization, alongside broader ethical considerations for a truly autonomous and human-centered future in robotics.