Abstract
This review explores the integration of artificial intelligence (AI) in mobile health applications for diabetes care. It focuses on key AI methodologies - machine learning, deep learning, and natural language processing - and their roles in glucose monitoring, personalized self-management, risk prediction, and clinical decision support. Drawing on recent literature (2018-2024), the study outlines the benefits of AI in improving accuracy, engagement, and precision in diabetes treatment. Challenges such as data privacy, algorithmic bias, and regulatory barriers are also examined. A new section discusses when AI technologies may become burdensome, especially in low-resource settings or for users with limited digital literacy. The review concludes with directions for enhancing model explainability and integrating AI with wearable and Internet of Things devices, emphasizing the need for ethical and equitable implementation in future diabetes management strategies.