This book presents a comprehensive framework for integrating artificial intelligence into Internet of Things (IoT) networks. It redefines communication paradigms by merging traditional data transmission with intelligent decision-making, adaptive feedback mechanisms, and semantic understanding. This book begins with foundational communication principles. Then it progresses to advanced topics such as AI-enabled feedback coding, semantic representation, multi-agent learning for multiple access, and intelligent network control through deep reinforcement learning, graph neural networks and large language models.  A central theme of this book illustrates how AI can unlock new dimensions in energy efficiency, scalability, and reliability across diverse IoT environments, from industrial automation and healthcare to smart cities and edge learning. Practical case studies and technical deep dives demonstrate how intelligent protocols improve communication quality, reduce energy consumption, and coordinate massive numbers of distributed devices. This book concludes with a forward-looking discussion on societal and ethical implications, highlighting challenges in managing intelligent IoT systems at scale.  This book targets researchers and graduate students and professionals focused on wireless communications, AI for networking and IoT systems. System engineers and practitioners working in 5G/6G, network optimization, industrial IoT and smart city development will also find this book useful.