안과용 AI 시장 규모, 점유율, 동향 분석 보고서 : 용도별, 전개 모드별, 기술별, 최종 용도별, 지역별, 부문별 예측(2025-2030년)

AI In Ophthalmology Market Summary

The global AI in ophthalmology market size was estimated at USD 209.23 million in 2024 and is projected to reach USD 1.36 billion by 2030, growing at a CAGR of 36.79% from 2025 to 2030. 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.

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, Grand View Research 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

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definitions
  • 1.2.1. Application Segment
  • 1.2.2. Deployment Mode Segment
  • 1.2.3. Technology Segment
  • 1.2.4. End Use
• 1.3. Information analysis
  • 1.3.1. Market formulation & data visualization
• 1.4. Data validation & publishing
• 1.5. Information Procurement
  • 1.5.1. Primary Research
• 1.6. Information or Data Analysis
• 1.7. Market Formulation & Validation
• 1.8. Market Model
• 1.9. Total Market: CAGR Calculation
• 1.10. Objectives
  • 1.10.1. Objective 1
  • 1.10.2. Objective 2

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Snapshot
• 2.3. Competitive Insights Landscape

Chapter 3. AI in Ophthalmology Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook.
• 3.2. Market Dynamics
  • 3.2.1. Market driver analysis
    • 3.2.1.1. Rising prevalence of eye diseases and diabetes
    • 3.2.1.2. Advancements in imaging technology
    • 3.2.1.3. Expansion of teleophthalmology services
  • 3.2.2. Market restraint analysis
    • 3.2.2.1. Data security and privacy concerns
    • 3.2.2.2. High integration costs
  • 3.2.3. Market opportunity analysis
  • 3.2.4. Market challenges analysis
• 3.3. Case Studies
• 3.4. AI in Ophthalmology Market Analysis Tools
  • 3.4.1. Industry Analysis - Porter's Five Forces Analysis
    • 3.4.1.1. Supplier power
    • 3.4.1.2. Buyer power
    • 3.4.1.3. Substitution threat
    • 3.4.1.4. Threat of new entrant
    • 3.4.1.5. Competitive rivalry
  • 3.4.2. PESTEL Analysis
    • 3.4.2.1. Political landscape
    • 3.4.2.2. Technological landscape
    • 3.4.2.3. Economic landscape
    • 3.4.2.4. Environmental Landscape
    • 3.4.2.5. Legal Landscape
    • 3.4.2.6. Social Landscape

Chapter 4. AI in Ophthalmology Market: Application Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global AI in Ophthalmology Market Application Movement Analysis
• 4.3. Global AI in Ophthalmology Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
• 4.4. Disease Detection and Monitoring
  • 4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 4.4.2. Retinal Disease Detection
    • 4.4.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 4.4.2.2. Diabetic Retinopathy (DR)
      • 4.4.2.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 4.4.2.3. Diabetic Macular Edema (DME)
      • 4.4.2.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 4.4.2.4. Age-related Macular Degeneration (AMD)
      • 4.4.2.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
    • 4.4.2.5. Retinal Vein Occlusion (RVO)
      • 4.4.2.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 4.4.3. Glaucoma Detection & Monitoring
    • 4.4.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 4.5. Surgical Planning & Outcome Prediction
  • 4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 4.6. AI for Ophthalmic Imaging Workflow Automation
  • 4.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 4.7. Others
  • 4.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 5. AI in Ophthalmology Market: Deployment Mode Estimates & Trend Analysis

• 5.1. Segment Dashboard
• 5.2. Global AI in Ophthalmology Market Deployment Mode Movement Analysis
• 5.3. Global AI in Ophthalmology Market Size & Trend Analysis, by Deployment Mode, 2018 to 2030 (USD Million)
• 5.4. On Premise
  • 5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 5.5. Cloud-based
  • 5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 6. AI in Ophthalmology Market: Technology Estimates & Trend Analysis

• 6.1. Segment Dashboard
• 6.2. Global AI in Ophthalmology Market Technology Movement Analysis
• 6.3. Global AI in Ophthalmology Market Size & Trend Analysis, by Technology, 2018 to 2030 (USD Million)
• 6.4. Machine Learning
  • 6.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.2. Deep learning
    • 6.4.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.3. Supervised
    • 6.4.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.4. Unsupervised
    • 6.4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.5. Others
    • 6.4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.5. Natural Language Processing
  • 6.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.2. Clinical Documentation Assistance
    • 6.5.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.3. OCR (Optical Character Recognition)
    • 6.5.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.4. Auto-coding of Ophthalmology Notes
    • 6.5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.5. Text Analytics for diagnostic reasoning
    • 6.5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.6. Voice-based Diagnostic Recording (Speech-to-Text)
    • 6.5.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.6. Context-Aware Computing
  • 6.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.7. Computer Vision
  • 6.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 7. AI in Ophthalmology Market: End Use Estimates & Trend Analysis

• 7.1. Segment Dashboard
• 7.2. Global AI in Ophthalmology Market End Use Movement Analysis
• 7.3. Global AI in Ophthalmology Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
• 7.4. Hospitals
  • 7.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.5. Specialty Ophthalmology Clinics
  • 7.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.6. Academic & Research Institutions
  • 7.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.7. Payers and Insurance Firms
  • 7.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.8. Others
  • 7.8.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 8. AI in Ophthalmology Market: Regional Estimates & Trend Analysis

• 8.1. Regional Market Share Analysis, 2024 & 2030
• 8.2. Regional Market Dashboard
• 8.3. Market Size & Forecasts Trend Analysis, 2018 to 2030:
• 8.4. North America
  • 8.4.1. U.S.
    • 8.4.1.1. Key country dynamics
    • 8.4.1.2. Regulatory framework
    • 8.4.1.3. Competitive scenario
    • 8.4.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.4.2. Canada
    • 8.4.2.1. Key country dynamics
    • 8.4.2.2. Regulatory framework
    • 8.4.2.3. Competitive scenario
    • 8.4.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.4.3. Mexico
    • 8.4.3.1. Key country dynamics
    • 8.4.3.2. Regulatory framework
    • 8.4.3.3. Competitive scenario
    • 8.4.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
• 8.5. Europe
  • 8.5.1. UK
    • 8.5.1.1. Key country dynamics
    • 8.5.1.2. Regulatory framework
    • 8.5.1.3. Competitive scenario
    • 8.5.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.2. Germany
    • 8.5.2.1. Key country dynamics
    • 8.5.2.2. Regulatory framework
    • 8.5.2.3. Competitive scenario
    • 8.5.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.3. France
    • 8.5.3.1. Key country dynamics
    • 8.5.3.2. Regulatory framework
    • 8.5.3.3. Competitive scenario
    • 8.5.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.4. Italy
    • 8.5.4.1. Key country dynamics
    • 8.5.4.2. Regulatory framework
    • 8.5.4.3. Competitive scenario
    • 8.5.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.5. Spain
    • 8.5.5.1. Key country dynamics
    • 8.5.5.2. Regulatory framework
    • 8.5.5.3. Competitive scenario
    • 8.5.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.6. Norway
    • 8.5.6.1. Key country dynamics
    • 8.5.6.2. Regulatory framework
    • 8.5.6.3. Competitive scenario
    • 8.5.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.7. Sweden
    • 8.5.7.1. Key country dynamics
    • 8.5.7.2. Regulatory framework
    • 8.5.7.3. Competitive scenario
    • 8.5.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.5.8. Denmark
    • 8.5.8.1. Key country dynamics
    • 8.5.8.2. Regulatory framework
    • 8.5.8.3. Competitive scenario
    • 8.5.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
• 8.6. Asia Pacific
  • 8.6.1. Japan
    • 8.6.1.1. Key country dynamics
    • 8.6.1.2. Regulatory framework
    • 8.6.1.3. Competitive scenario
    • 8.6.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.6.2. China
    • 8.6.2.1. Key country dynamics
    • 8.6.2.2. Regulatory framework
    • 8.6.2.3. Competitive scenario
    • 8.6.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.6.3. India
    • 8.6.3.1. Key country dynamics
    • 8.6.3.2. Regulatory framework
    • 8.6.3.3. Competitive scenario
    • 8.6.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.6.4. Australia
    • 8.6.4.1. Key country dynamics
    • 8.6.4.2. Regulatory framework
    • 8.6.4.3. Competitive scenario
    • 8.6.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.6.5. South Korea
    • 8.6.5.1. Key country dynamics
    • 8.6.5.2. Regulatory framework
    • 8.6.5.3. Competitive scenario
    • 8.6.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.6.6. Thailand
    • 8.6.6.1. Key country dynamics
    • 8.6.6.2. Regulatory framework
    • 8.6.6.3. Competitive scenario
    • 8.6.6.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
• 8.7. Latin America
  • 8.7.1. Brazil
    • 8.7.1.1. Key country dynamics
    • 8.7.1.2. Regulatory framework
    • 8.7.1.3. Competitive scenario
    • 8.7.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.7.2. Argentina
    • 8.7.2.1. Key country dynamics
    • 8.7.2.2. Regulatory framework
    • 8.7.2.3. Competitive scenario
    • 8.7.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
• 8.8. MEA
  • 8.8.1. South Africa
    • 8.8.1.1. Key country dynamics
    • 8.8.1.2. Regulatory framework
    • 8.8.1.3. Competitive scenario
    • 8.8.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.8.2. Saudi Arabia
    • 8.8.2.1. Key country dynamics
    • 8.8.2.2. Regulatory framework
    • 8.8.2.3. Competitive scenario
    • 8.8.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.8.3. UAE
    • 8.8.3.1. Key country dynamics
    • 8.8.3.2. Regulatory framework
    • 8.8.3.3. Competitive scenario
    • 8.8.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
  • 8.8.4. Kuwait
    • 8.8.4.1. Key country dynamics
    • 8.8.4.2. Regulatory framework
    • 8.8.4.3. Competitive scenario
    • 8.8.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 9. Competitive Landscape

• 9.1. Company/Competition Categorization
• 9.2. Strategy Mapping
• 9.3. Company Market Position Analysis, 2024
• 9.4. Company Profiles/Listing
  • 9.4.1. OphtAI
    • 9.4.1.1. Company overview
    • 9.4.1.2. Financial performance
    • 9.4.1.3. Technology type benchmarking
    • 9.4.1.4. Strategic initiatives
  • 9.4.2. Eyenuk, Inc.
    • 9.4.2.1. Company overview
    • 9.4.2.2. Financial performance
    • 9.4.2.3. Technology type benchmarking
    • 9.4.2.4. Strategic initiatives
  • 9.4.3. Google LLC
    • 9.4.3.1. Company overview
    • 9.4.3.2. Financial performance
    • 9.4.3.3. Technology type benchmarking
    • 9.4.3.4. Strategic initiatives
  • 9.4.4. IBM Corporation
    • 9.4.4.1. Company overview
    • 9.4.4.2. Financial performance
    • 9.4.4.3. Technology type benchmarking
    • 9.4.4.4. Strategic initiatives
  • 9.4.5. Optos plc
    • 9.4.5.1. Company overview
    • 9.4.5.2. Financial performance
    • 9.4.5.3. Technology type benchmarking
    • 9.4.5.4. Strategic initiatives
  • 9.4.6. Zeiss
    • 9.4.6.1. Company overview
    • 9.4.6.2. Financial performance
    • 9.4.6.3. Technology type benchmarking
    • 9.4.6.4. Strategic initiatives
  • 9.4.7. Topcon Healthcare
    • 9.4.7.1. Company overview
    • 9.4.7.2. Financial performance
    • 9.4.7.3. Technology type benchmarking
    • 9.4.7.4. Strategic initiatives
  • 9.4.8. Ikerian AG (RetinAi)
    • 9.4.8.1. Company overview
    • 9.4.8.2. Financial performance
    • 9.4.8.3. Technology type benchmarking
    • 9.4.8.4. Strategic initiatives
  • 9.4.9. Nidek Co., Ltd.
    • 9.4.9.1. Company overview
    • 9.4.9.2. Financial performance
    • 9.4.9.3. Technology type benchmarking
    • 9.4.9.4. Strategic initiatives
  • 9.4.10. Altris AI
    • 9.4.10.1. Company overview
    • 9.4.10.2. Financial performance
    • 9.4.10.3. Technology type benchmarking
    • 9.4.10.4. Strategic initiatives
  • 9.4.11. Remidio Innovative Solutions Pvt Ltd.
    • 9.4.11.1. Company overview
    • 9.4.11.2. Financial performance
    • 9.4.11.3. Technology type benchmarking
    • 9.4.11.4. Strategic initiatives
  • 9.4.12. Oculus Maxima LIMITED
    • 9.4.12.1. Company overview
    • 9.4.12.2. Financial performance
    • 9.4.12.3. Technology type benchmarking
    • 9.4.12.4. Strategic initiatives
  • 9.4.13. Siemens Healthineers
    • 9.4.13.1. Company overview
    • 9.4.13.2. Financial performance
    • 9.4.13.3. Technology type benchmarking
    • 9.4.13.4. Strategic initiatives
  • 9.4.14. Haag-Streit Group
    • 9.4.14.1. Company overview
    • 9.4.14.2. Financial performance
    • 9.4.14.3. Technology type benchmarking
    • 9.4.14.4. Strategic initiatives