The IoT has revolutionized how devices, data, and services interact, bridging the physical and digital worlds. This chapter introduces the fundamental principles of IoT communication, outlining its core components, networking technologies, and evolutionary trajectory. From early machine-to-machine (M2M) systems to Narrowband IoT (NB-IoT), Long Range Wide Area Network (LoRaWAN), and 5G/6G, IoT has undergone significant transformations to meet the demands of real-time, large-scale data exchange. In parallel, Artificial Intelligence (AI) has emerged as a powerful tool for enhancing IoT systems by enabling intelligent automation, predictive analytics, and decision-making capabilities. The chapter provides an overview of AI’s evolution, key principles, and major milestones, with a focus on deep learning, reinforcement learning, and neural networks. The chapter also highlights the synergy between AI and IoT, demonstrating how AI empowers IoT networks to be more autonomous, scalable, and adaptive. The introduction concludes with an outline of the book’s structure, detailing how AI-driven IoT communication techniques—such as feedback communication, semantic communication, multiple access, and network control—will be explored in subsequent chapters. This sets the stage for understanding how AI transforms IoT from a passive data collector into an intelligent, self-optimizing ecosystem.