Purpose: The purpose of this study was to evaluate economic aspect of diabetic retinopathy (DR) screening strategies in developing countries. It focused on the cost-effectiveness of artificial intelligence (AI) and telemedicine compared to standard care. Methods: A structured literature search was conducted using PubMed, ScienceDirect, the Cochrane Library, and Google Scholar. Studies were included if they involved patients with type 1 or type 2 diabetes mellitus, conducted in low- or middle-income countries at the time of the study, compared AI or telemedicine-based intervention with standard care, and performed a health economic assessment or provided sufficient data to assess cost-effectiveness. Results: Seven studies were identified from China, Thailand, Brazil, and India. Of these, four applied cost-utility analysis, two used cost-effectiveness analysis, and one employed both approaches. Three studies evaluated AI-based screening, three focused on telemedicine, and one examined a combined AI-assisted telemedicine model. All studies compared these interventions to standard care, with some using no screening as the comparator. Across all studies, AI and telemedicine-based screening strategies were found to be cost-effective, though the degree of economic benefit varied depending on the model, setting, and assumptions used. Conclusions This review supports the cost-effectiveness and feasibility of AI- and telemedicine-based DR screening in developing countries. While most strategies proved economically viable, cost savings and health gains varied. Screening frequency and patient compliance were key factors influencing successful implementation.