The concept of precision medicine has emerged as a promising approach in diabetes management. Researchers have made substantial progress in understanding the genetic and molecular underpinnings of diabetes subtypes. By identifying specific genetic markers and characterizing phenotypes, personalized treatment plans can be tailored to an individual's unique needs. Precision medicine holds great potential for optimizing glycemic control, minimizing complications and improving overall patient outcomes. The integration of artificial intelligence and machine learning techniques has revolutionized diabetes research and clinical practice. AI algorithms can analyze vast amounts of data, including electronic health records, genetic information and lifestyle factors, to provide personalized predictions and treatment recommendations. These technologies empower healthcare professionals with valuable tools for early detection, risk stratification and optimal therapy selection, ultimately leading to improved patient care and outcomes [2].