Artificial intelligence (AI) is transforming glaucoma care by enhancing screening, diagnosis, management, and progression detection. Glaucoma, a leading cause of irreversible blindness, requires early detection and lifelong treatment. AI technologies, including machine learning and deep learning, are now being integrated into clinical practices to improve accuracy, efficiency, and personalization in glaucoma care. AI-powered systems analyze retinal photographs, optical coherence tomography (OCT), and visual field tests to identify high-risk patients and detect glaucomatous patterns. These systems also enable continuous monitoring, alerting physicians to rapid disease progression through longitudinal data analysis. AI can guide precision medicine by integrating predictive analytics with patient-specific parameters, leading to individualized treatment strategies. Additionally, AI is being used in robotic surgery and computer-based guidance to improve surgical outcomes and training. Beyond the clinic, AI chatbots and reminder systems can assist in patient education and medication adherence. However, challenges remain in ensuring clinical integration, usability, diversity, and ethical considerations. The review highlights AI's vast capabilities in transforming glaucoma care, emphasizing key achievements, future prospects, and practical considerations for advancing from bench to bedside. AI's potential in glaucoma care is vast, with ongoing research exploring its role in screening, diagnosis, disease progression prediction, and personalized treatment. As AI continues to evolve, it holds promise for improving patient outcomes and expanding access to care, particularly in low-resource settings. The integration of AI into glaucoma care requires careful validation, addressing data integrity, and ensuring ethical and practical implementation.Artificial intelligence (AI) is transforming glaucoma care by enhancing screening, diagnosis, management, and progression detection. Glaucoma, a leading cause of irreversible blindness, requires early detection and lifelong treatment. AI technologies, including machine learning and deep learning, are now being integrated into clinical practices to improve accuracy, efficiency, and personalization in glaucoma care. AI-powered systems analyze retinal photographs, optical coherence tomography (OCT), and visual field tests to identify high-risk patients and detect glaucomatous patterns. These systems also enable continuous monitoring, alerting physicians to rapid disease progression through longitudinal data analysis. AI can guide precision medicine by integrating predictive analytics with patient-specific parameters, leading to individualized treatment strategies. Additionally, AI is being used in robotic surgery and computer-based guidance to improve surgical outcomes and training. Beyond the clinic, AI chatbots and reminder systems can assist in patient education and medication adherence. However, challenges remain in ensuring clinical integration, usability, diversity, and ethical considerations. The review highlights AI's vast capabilities in transforming glaucoma care, emphasizing key achievements, future prospects, and practical considerations for advancing from bench to bedside. AI's potential in glaucoma care is vast, with ongoing research exploring its role in screening, diagnosis, disease progression prediction, and personalized treatment. As AI continues to evolve, it holds promise for improving patient outcomes and expanding access to care, particularly in low-resource settings. The integration of AI into glaucoma care requires careful validation, addressing data integrity, and ensuring ethical and practical implementation.