Osteoporosis is a systemic skeletal disease characterized by decreased bone mass, impaired bone microarchitecture, and increased fracture susceptibility, which increases the risk of functional disability and mortality. The disease has a complex pathophysiology, chronic progression and often asymptomatic course, which complicates diagnosis and treatment. Artificial intelligence technologies integrate radiomics and multiomics data to create intelligent frameworks that map disease progression, identify molecular biomarkers, and stratify individual risk. AI supports accurate diagnosis, preventive monitoring and personalized interventions at the molecular level. AI models have also been developed to predict drug targets and assess therapeutic response, enabling new drug discovery mechanisms. The study describes the application of AI in the management of osteoporosis through technological breakthroughs in basic and clinical research. These advances optimize preventive monitoring, accurate diagnosis, personalized treatment decisions and molecularly targeted drug discovery. AI thus provides the theoretical foundation and practical pathways for precision and personalized medicine.