Automatic Milking Systems (AMS) have revolutionized dairy farming by automating the milking process, improving efficiency, reducing labor, and enhancing farm management. AMS technology, integrated with sensors and machine learning algorithms, enables real-time monitoring of cow health and productivity, optimizing the milking process. This study explores advancements in AMS, focusing on key technological components such as robotic milking, sensor systems, and predictive data analytics. Studies demonstrate that AMS improves labor efficiency, cow welfare, and overall farm profitability. However, the adoption of AMS is challenged by high initial investment costs, the need for cow adaptation, and technological learning curves for farmers. Future advancements in sensor technology, data processing, and machine learning will enhance AMS's reliability and accessibility, particularly for small-scale farmers. This study highlights AMS's potential to contribute to sustainable and humane dairy farming practices while addressing current limitations and identifying opportunities for future research.