Implementing AI in healthcare presents several challenges, including data privacy, integration with existing systems, and the need for robust training data. Privacy concerns arise due to sensitive medical records, necessitating strict compliance with regulations like HIPAA. Additionally, many healthcare systems utilize legacy technology, making integration a complex and resource-intensive process. There is also a shortage of high-quality, annotated data needed to train AI algorithms effectively, which can hinder the development of reliable applications. Finally, the ethical implications of AI decision-making in patient care present ongoing debates in the field.