The integration of Machine Learning (ML) and Artificial Intelligence (AI) in Internet of Things (IoT) systems has revolutionized various industries by enabling intelligent decision-making and automation. This paper presents an overview of integration techniques and applications of ML and AI in IoT environments. We discuss the challenges and opportunities associated with the fusion of these technologies, including data management, computational complexity, and privacy concerns. Furthermore, we explore various integration approaches such as edge computing, federated learning, and distributed intelligence architectures to address these challenges. We also highlight a range of IoT applications leveraging ML and AI techniques, including predictive maintenance, anomaly detection, smart healthcare, and environmental monitoring. Finally, we identify future research directions and emerging trends in this rapidly evolving field.