Artificial intelligence (AI) is now shaping the future of eye care practices by making optometric procedures more efficient and sustainable than ever. Abstract discusses the incorporation of optometry advancements via AI and how these changes can be done in a more sustainable manner. AI-based diagnostic methods such as deep learning algorithms are reducing the requirements for resource-demanding procedures in diagnosing diseases that can be diagnosed earlier (e.g., diabetic retinopathy, glaucoma). Teleoptometry, for example, leverages AI support tofacilitate remote eye exams that allow patients to avoid traveling. Examples of personalized treatments are AI-customized lenses (or smart lenses) and myopia management that not only minimizes material waste but also enhances the precision of treatment. An in-depth analysis of the existing research was conducted, and 16 research articles were selected focusing on the applications of (AI) in optometry-particularly in telemedicine, personalized care, diagnostics, and sustainable practices. This process involved reviewing research papers to assess how AI could influence the productivity, resource use, and environmental footprint of optometric practices. The findings indicate that AI-driven diagnostic tools, such as deep learning algorithms for analyzing retinal scans, significantly improve the early detection of conditions like glaucoma and diabetic retinopathy. This reduces the necessity for additional patient visits, leading to resource savings. Recent advancements in artificial intelligence (AI) within optometry offer two key advantages: enhancing the quality of patient care and promoting sustainability by reducing waste, optimizing resource use, and minimizing environmental impact. By incorporating AI into their diagnostic, treatment, and management processes, optometry practices can significantly support sustainable healthcare models.