The AI in Ophthalmology Market was valued at USD 209.23 million in 2024, and is projected to reach USD 1.36 billion by 2030, rising at a CAGR of 36.79%. The rising prevalence of eye diseases, advancements in imaging technology, and expansion of teleophthalmology services are factors contributing to market growth.
In addition, growing preference for personalized treatment plans and increasing government initiatives fuel market growth further. The increasing prevalence of eye-related conditions, such as diabetic retinopathy, age-related macular degeneration (AMD), and glaucoma, is a significant factor driving the adoption of AI in ophthalmology. As the population ages, the incidence of these diseases increases, creating a need for efficient and accurate diagnostic tools. For instance, according to the CDC, the estimated number of Americans living with glaucoma in 2022 was 4.22 million. AI algorithms can rapidly analyze complex retinal images, facilitating early detection and treatment. For instance, AI systems have shown high sensitivity and specificity in identifying diabetic retinopathy, which allows for timely interventions and reduces the risk of vision loss.
Moreover, integrating advanced imaging techniques such as Optical Coherence Tomography (OCT) with AI has revolutionized ophthalmic diagnostics. High-resolution imaging provides detailed views of ocular structures, which enhances diagnostic precision when analyzed by artificial intelligence (AI). The availability of large datasets from these imaging technologies allows for the training of robust AI models, improving their accuracy and reliability in clinical settings. For instance, researchers at the Chinese University of Hong Kong (CUHK) have developed VisionFM, an advanced AI ophthalmic imaging foundation model. Trained on 3.4 million images across eight modalities, VisionFM diagnoses multiple eye diseases and uniquely predicts intracranial tumors from retinal images.
Furthermore, teleophthalmology, the remote delivery of eye care services, has gained traction, especially in underserved regions. AI is crucial in this expansion by enabling automated analysis of retinal images, facilitating remote diagnosis, and reducing the need for in-person consultations. This approach increases access to eye care and optimizes resource utilization in healthcare systems. For instance, in June 2024, C3 Med-Tech, an ophthalmic health tech startup, raised USD 0.23 million to launch AI-enabled, portable eye screening devices. The funding is expected to support telemedicine integration, real-time disease detection, and expansion across India, aiming to reduce avoidable blindness, especially in underserved communities facing a shortage of ophthalmologists.
Moreover, AI's ability to analyze and interpret data from Electronic Health Records (EHRs) facilitates personalized treatment plans in ophthalmology. AI predicts disease progression by assessing patient history, genetic information, and imaging data and recommends tailored interventions, further contributing to market growth.
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In addition, growing preference for personalized treatment plans and increasing government initiatives fuel market growth further. The increasing prevalence of eye-related conditions, such as diabetic retinopathy, age-related macular degeneration (AMD), and glaucoma, is a significant factor driving the adoption of AI in ophthalmology. As the population ages, the incidence of these diseases increases, creating a need for efficient and accurate diagnostic tools. For instance, according to the CDC, the estimated number of Americans living with glaucoma in 2022 was 4.22 million. AI algorithms can rapidly analyze complex retinal images, facilitating early detection and treatment. For instance, AI systems have shown high sensitivity and specificity in identifying diabetic retinopathy, which allows for timely interventions and reduces the risk of vision loss.
Moreover, integrating advanced imaging techniques such as Optical Coherence Tomography (OCT) with AI has revolutionized ophthalmic diagnostics. High-resolution imaging provides detailed views of ocular structures, which enhances diagnostic precision when analyzed by artificial intelligence (AI). The availability of large datasets from these imaging technologies allows for the training of robust AI models, improving their accuracy and reliability in clinical settings. For instance, researchers at the Chinese University of Hong Kong (CUHK) have developed VisionFM, an advanced AI ophthalmic imaging foundation model. Trained on 3.4 million images across eight modalities, VisionFM diagnoses multiple eye diseases and uniquely predicts intracranial tumors from retinal images.
Furthermore, teleophthalmology, the remote delivery of eye care services, has gained traction, especially in underserved regions. AI is crucial in this expansion by enabling automated analysis of retinal images, facilitating remote diagnosis, and reducing the need for in-person consultations. This approach increases access to eye care and optimizes resource utilization in healthcare systems. For instance, in June 2024, C3 Med-Tech, an ophthalmic health tech startup, raised USD 0.23 million to launch AI-enabled, portable eye screening devices. The funding is expected to support telemedicine integration, real-time disease detection, and expansion across India, aiming to reduce avoidable blindness, especially in underserved communities facing a shortage of ophthalmologists.
Moreover, AI's ability to analyze and interpret data from Electronic Health Records (EHRs) facilitates personalized treatment plans in ophthalmology. AI predicts disease progression by assessing patient history, genetic information, and imaging data and recommends tailored interventions, further contributing to market growth.
Global AI In Ophthalmology Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, the analyst has segmented the global AI in ophthalmology market report based on application, deployment mode, technology, end-use, and region.Application Outlook (Revenue, USD Million, 2018-2030)
- Disease Detection and Monitoring
- Retinal Disease Detection
- Diabetic Retinopathy (DR)
- Diabetic Macular Edema (DME)
- Age-related Macular Degeneration (AMD)
- Retinal Vein Occlusion (RVO)
- Glaucoma Detection & Monitoring
- Surgical Planning & Outcome Prediction
- AI for Ophthalmic Imaging Workflow Automation
- Others
Deployment Mode Outlook (Revenue, USD Million, 2018-2030)
- On Premise
- Cloud-based
Technology Outlook (Revenue, USD Million, 2018-2030)
- Machine Learning
- Deep learning
- Supervised
- Unsupervised
- Others
- Natural Language Processing
- Clinical Documentation Assistance
- OCR (Optical Character Recognition)
- Auto-coding of Ophthalmology Notes
- Text Analytics for Diagnostic Reasoning
- Voice-based Diagnostic Recording (Speech-to-Text)
- Context-Aware Computing
- Computer Vision
End-use Outlook (Revenue, USD Million, 2018-2030)
- Hospitals
- Specialty Ophthalmology Clinics
- Academic & Research Institutions
- Payers & Insurance Companies
- Others
Regional Outlook (Revenue, USD Million, 2018-2030)
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- UK
- France
- Italy
- Spain
- Denmark
- Sweden
- Norway
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia
- Thailand
- Latin America
- Brazil
- Argentina
- MEA
- South Africa
- Saudi Arabia
- UAE
- Kuwait
This report addresses:
- Market intelligence to enable effective decision-making
- Market estimates and forecasts from 2018 to 2030
- Growth opportunities and trend analyses
- Segment and regional revenue forecasts for market assessment
- Competition strategy and market share analysis
- Product innovation listings for you to stay ahead of the curve
Why Should You Buy This Report?
- Comprehensive Market Analysis: Gain detailed insights into the market across major regions and segments.
- Competitive Landscape: Explore the market presence of key players.
- Future Trends: Discover the pivotal trends and drivers shaping the future of the market.
- Actionable Recommendations: Utilize insights to uncover new revenue streams and guide strategic business decisions.
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Table of Contents
Chapter 1. Methodology and Scope
Chapter 2. Executive Summary
Chapter 3. AI in Ophthalmology Market Variables, Trends & Scope
Chapter 4. AI in Ophthalmology Market: Application Estimates & Trend Analysis
Chapter 5. AI in Ophthalmology Market: Deployment Mode Estimates & Trend Analysis
Chapter 6. AI in Ophthalmology Market: Technology Estimates & Trend Analysis
Chapter 7. AI in Ophthalmology Market: End Use Estimates & Trend Analysis
Chapter 8. AI in Ophthalmology Market: Regional Estimates & Trend Analysis
Chapter 9. Competitive Landscape
List of Tables
List of Figures
Companies Mentioned
The major companies featured in this AI in Ophthalmology market report include:- OphtAI
- Eyenuk, Inc.
- Google LLC
- IBM Corporation
- Optos plc
- Zeiss
- Topcon Healthcare
- Ikerian AG (RetinAi)
- Nidek Co., Ltd.
- Altris AI
- Remidio Innovative Solutions Pvt Ltd.
- Oculus Maxima LIMITED
- Siemens Healthineers
- Haag-Streit Group
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 120 |
| Published | May 2025 |
| Forecast Period | 2024 - 2030 |
| Estimated Market Value ( USD | $ 209.23 Million |
| Forecasted Market Value ( USD | $ 1360 Million |
| Compound Annual Growth Rate | 36.7% |
| Regions Covered | Global |
| No. of Companies Mentioned | 15 |
