Role of Artificial Intelligence in Diabetes Care: Present Uses, Limitations, and Future Directions

The global health burden of diabetes mellitus remains high, and fresh approaches are required beyond traditional medical management. Artificial intelligence (AI) has recently become a groundbreaking catalyst with great potential for revolutionizing all aspects of diabetes care, from forecasting and diagnosis to personalized therapy and risk prevention. This review discusses the use of machine learning, deep learning and algorithms derived from data analysis for the development of diabetes prediction, screening and continuous glucose monitoring. AI-enhanced methods for early identification of high-risk patients, management of insulin dosage and nutritional planning based on an individual’s dietary and physical activity patterns using adaptive digital platforms are also developed. Further, smart systems integrated with wearable biosensors and telemedicine applications have enabled patient-centric as well as remote and continuous management. The article also points out AI’s increasingly prominent application in automatic dietary monitoring, health education as well as early detection of diabetic complications including retinopathy and nephropathy. Although progress has been made in all of these areas, concerns including privacy, suboptimal-digital-literacy, algorithmic bias and regulatory barriers are some of the obstacles to widespread clinical implementation. Looking forward AI will be integrated with the Internet of Medical Things, generative and language models and precision-medicine frameworks to deliver safer, more equitable and effective diabetes care. Overall, AI represents a pivotal innovation that promises to shift diabetes management toward a predictive, preventive, and personalized healthcare paradigm.