Background: Ayurvedic ophthalmology (Shalakyatantra) offers personalized frameworks for diagnosing Netra Rogas through constitutional assessment. Artificial intelligence (AI) has demonstrated high accuracy in ophthalmic image analysis. This review examines the convergence of AI with Ayurvedic ophthalmology for predictive diagnosis and personalized eye care. Methods: A narrative synthesis of peer-reviewed literature (2018–2026) on AI applications in ophthalmology and Ayurvedic diagnostic systems, including deep learning for retinal image analysis, AI-based Prakriti assessment, and predictive models, was conducted-. Key findings: Deep learning systems achieved high diagnostic accuracy for diabetic retinopathy (sensitivity, 97.5%; specificity, 96.1%), glaucoma (AUROC, 0.996), and age-related- macular degeneration progression. AI-enabled- Nadi Pariksha systems have demonstrated 85–95% accuracy in Prakriti determination. Conclusions: The convergence of AI-driven- diagnostics with Ayurvedic personalized medicine offers substantial opportunities for predictive, preventive, and participatory eye care. Standardized datasets, explainable AI, prospective validation, and culturally informed regulations are required.