The rapid advancement and progress of IoT devices is creating an urgent need for efficient power management strategies, particularly in battery-powered and remote applications. Traditional power-saving methods often fall short in dynamic, data-intensive environments. This chapter explores the integration of AI techniques to enable intelligent, adaptive power management in IoT systems. The AI is itself an integration of ML (machine learning), DL (deep learning), FL (federated learning), and RL (reinforcement learning); therefore, this chapter uses artificial intelligence as a combination of ML&DL&FL or ML&DL&RL.