AbstractChronic diseases such as diabetes, heart disease, cancer, and respiratory conditions are increasing globally, placing serious strain on healthcare systems—especially in low- and middle-income countries. Limited resources, underfunded infrastructure, and staff shortages make it difficult to provide timely and consistent care. As more people live with these long-term conditions, the demand for early diagnosis and continuous monitoring continues to grow. This study explores how Artificial Intelligence (AI) can support healthcare providers in managing chronic illnesses more efficiently. It focuses on practical tools such as pattern-recognition software, medical image analysis programs, and wearable devices that track patients' health. Using a quantitative approach, the research reviewed over 20,000 anonymized patient records from the United States and Brazil. It examined three common chronic conditions: type 2 diabetes, heart disease, and COPD. The study compared outcomes before and after AI tools were introduced. Findings show a 28% drop in diagnostic errors and a 22% improvement in early detection. Wearables also helped reduce hospital readmissions. However, challenges like digital inequality and data fairness remain. With proper investment and policy support, AI can greatly improve chronic care. Keyword: Artificial Intelligence, Chronic Diseases, Diagnosis, Public Health, Wearable devices, Healthcare system.