The multidisciplinary approach significantly advances AI and ML applications by combining expertise from various fields, fostering innovation and addressing complex challenges. This integration allows for a more comprehensive understanding of problems and the development of more robust solutions. For instance, in healthcare, AI systems for disease detection and treatment benefit from collaboration between AI experts, medical professionals, and biomedical researchers. This interdisciplinary approach has led to AI algorithms that can diagnose diseases like cancer and Alzheimer's with high accuracy, and even assist in personalized medicine and drug discovery. Another example is in smart cities, where AI and ML are used for traffic prediction and congestion management, integrating data from transportation, IoT, and urban planning to optimize traffic flow and enhance public safety. This multidisciplinary approach ensures that AI and ML solutions are not only technically sound but also socially responsible and ethically aligned.