Access to clean and safe water is vital for communities worldwide, yet traditional water purification methods often fall short in efficiency and sustainability. This review addresses these challenges by examining the integration of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) in water purification processes. We propose leveraging these advanced technologies to enhance real-time monitoring, optimize filtration, and predict maintenance needs, thereby improving overall system performance and sustainability. Through an analysis of various methodologies, applications, and case studies, our findings demonstrate significant improvements in water quality management, operational efficiency, and environmental impact. Future perspectives highlight the need for continued research into advanced algorithms, scalable solutions, and robust security measures to fully realize the potential of AI, ML, and IoT in water purification systems.