AI-Driven Retinal Screening Device Market

Overview

The global AI-Driven Retinal Screening Device Market was valued at USD 2.1 billion in 2025 and is projected to reach USD 6.0 billion by 2034, growing at a CAGR of 12.3% during the forecast period (2026-2034). The market is driven by the rising global burden of diabetic retinopathy and other vision-threatening retinal disorders, the expansion of point-of-care screening infrastructure in primary care and community settings, and the increasing deployment of autonomous artificial intelligence software that delivers a diagnostic result without requiring a specialist grader at the first point of contact. The market is shifting from conventional, tele-grading workflows, where captured images are transmitted to a remote human reader for a delayed result, toward fully autonomous, point-of-care software that produces a diagnostic output within minutes of image capture. Manufacturers are also embedding inference directly onto handheld cameras so that grading can proceed without a stable internet connection, a design first proven in rural screening programs in India and now attracting interest from national screening bodies in higher-income markets.  Government initiatives such as the United Kingdom National Screening Committee's May 2026 public consultation on incorporating Automated Retinal Image Analysis Systems into the National Health Service Diabetic Eye Screening Programme, and the continued use of a dedicated Current Procedural Terminology code for autonomous point-of-care retinal artificial intelligence screening in the United States, are lowering the regulatory and reimbursement barriers that previously limited adoption outside specialist eye clinics. By region, North America held the largest share of the market in 2025, supported by broad reimbursement coverage, a dense base of FDA-cleared autonomous AI systems, and high diabetes prevalence. Asia Pacific is projected to be the fastest-growing region during the forecast period, propelled by national screening programs, large diabetic populations in China and India, and expanding deployment of low-cost, portable screening cameras.

Market Size & Share

Market Dynamics

KEY MARKET TREND

Shift Toward Fully Autonomous, Point-of-Care AI Screening Emerging as a Transformational Trend

• Healthcare providers are increasingly replacing tele-grading workflows, in which captured retinal images are sent to a remote human reader, with fully autonomous software that renders a diagnostic result at the point of care. This shift removes the multi-day turnaround associated with remote grading and allows primary care clinics, pharmacies, and community health centers to close a patient's screening gap within a single visit.
• Device developers are embedding inference directly on handheld fundus cameras so that screening can proceed without a stable internet connection, a capability first proven for rural and resource-limited settings. Offline, edge-based grading is reducing the operating cost of national screening drives and is beginning to shape procurement decisions in regions where broadband coverage remains inconsistent.
• Retinal screening platforms are expanding beyond diabetic retinopathy to flag glaucoma and age-related macular degeneration, and newer systems are estimating cardiovascular and chronic kidney disease risk from the same fundus image. This multi-disease positioning is widening the customer base for these devices from ophthalmology clinics into primary care, occupational health programs, and insurance-linked wellness screening.
• The UK National Screening Committee opened a public consultation in May 2026 on incorporating Automated Retinal Image Analysis Systems into the National Health Service Diabetic Eye Screening Programme, after an updated evidence review found that some automated systems perform as well as a first human grader. The outcome of this consultation is expected to influence automated-grading policy in other national screening programs.

KEY MARKET DRIVER

Rising Global Burden of Diabetic Retinopathy and Shortage of Retina Specialists is the Key Driver

• The expanding global population of people living with diabetes is enlarging the pool of patients who require an annual retinal examination, since roughly one in three people with diabetes eventually develops some degree of diabetic retinopathy. This growing at-risk population is outpacing the capacity of retina specialists to perform manual dilated eye examinations, creating structural, long-term demand for automated screening tools.
• Several of the largest diabetic populations globally are served by a very small pool of ophthalmologists relative to the patient base, a mismatch that makes universal annual dilated eye examination logistically difficult without shifting parts of the task to AI-assisted devices that non-specialist operators can run. Comparable workforce gaps are reported across parts of Sub-Saharan Africa and Southeast Asia, reinforcing demand for task-shifted screening models.
• Reimbursement support, including a dedicated Current Procedural Terminology code for autonomous, point-of-care retinal AI screening in the United States, has removed a major commercial barrier to primary care adoption by allowing practices to bill for AI-based diagnostic screening rather than absorbing it as an uncompensated service. Comparable reimbursement pathways are now emerging in South Korea and parts of the Gulf Cooperation Council.
• AEYE Health received FDA clearance in 2024 for a fully autonomous artificial intelligence system compatible with a handheld retinal camera, extending autonomous screening beyond the tabletop cameras that most earlier clearances relied on. The clearance is a practical example of how portable hardware and cleared AI software together are lowering the equipment barrier for smaller primary care practices.

KEY MARKET OPPORTUNITY

Expansion of Point-of-Care and Community-Based Screening Models in Underserved Regions Creating Significant Market Opportunity

• Portable, battery-operated fundus cameras paired with offline AI software are opening a large, previously unaddressed opportunity in rural and low-resource geographies where a fixed ophthalmology clinic is not economically viable. Mobile screening camps built around these devices can reach villages and small towns in a single day, converting what was previously undiagnosed disease into an identified and referable patient population.
• Retail pharmacy chains, workplace wellness programs, and optometry retail outlets represent a largely untapped distribution channel for retinal AI screening, since these locations already have high consumer footfall but historically lacked the specialist staff to perform a dilated eye examination. Extending screening into these channels can generate a new, high-volume referral pipeline for downstream ophthalmology and endocrinology care.
• Camera manufacturers and AI software developers are increasingly entering distribution partnerships rather than building a full stack independently, licensing a third-party AI engine onto their own imaging hardware to reach new geographies faster. This asset-light, partnership-based business model is lowering the capital required to enter new country markets and is broadening the number of AI vendors an imaging device can support.
• Forus Health's 3nethra retinal imaging platform has been used to screen more than 20 million patients across more than 75 countries, illustrating the scale that a single portable, AI-enabled screening device can reach in underserved markets when paired with public health screening programs. This track record is a reference point that other manufacturers cite when justifying investment in similar low-cost, high-volume screening models.

AI-Driven Retinal Screening Device Market Size, 2025-2034 (USD Billion)

Segmentation Analysis

Analysis by Technology

Fundus image-based AI held the largest market share in 2025 because it offers a lower-cost imaging pathway that is already familiar to eye care providers and primary care operators, and the large historical library of labeled fundus images has allowed developers to train and validate diagnostic algorithms faster than for any other retinal imaging modality. Regulatory clearances to date, including the earliest FDA-cleared autonomous systems, were built on fundus photography, giving this technology the deepest base of clinical evidence and reimbursement precedent, which continues to steer new hospital and primary care purchasing decisions toward fundus-based platforms even as newer imaging modalities enter the market.

Multimodal AI is projected to grow at the fastest CAGR during the forecast period. Combining fundus photography with optical coherence tomography or additional biomarker inputs allows a single examination to screen for diabetic retinopathy, glaucoma, and age-related macular degeneration together, which is attracting hospitals and diagnostic chains that want to consolidate multiple referral pathways into one device. Ongoing research collaborations between academic eye hospitals and AI developers are expanding multimodal algorithms toward systemic disease indicators such as cardiovascular and kidney risk, a capability that is expected to draw the fastest new investment through 2034.

Technology categories include

• Fundus Image-Based AI (Dominating Segment)
• Multimodal AI (Highest CAGR Segment)
• OCT-Based AI

Analysis by Component

Software held the largest market share in 2025 because the diagnostic algorithm is the component that carries most of the clinical value, the regulatory clearance, and the ongoing licensing revenue, while imaging hardware has become increasingly commoditized across multiple camera manufacturers that support the same third-party AI engines. Health systems that already own a compatible fundus or OCT camera can add AI grading purely through a software license or subscription, which has made software the largest revenue component even in markets where camera penetration is still developing.

Services is projected to grow at the fastest CAGR during the forecast period. As health systems and screening programs scale up deployment, demand is rising for implementation support, workflow integration, algorithm validation studies, and ongoing technical support contracts that accompany large multi-site rollouts. Manufacturers are increasingly bundling managed screening services, including camera maintenance and remote monitoring, with their software licenses, a model that is growing faster than one-time hardware or software sales as customers prefer predictable, outcome-linked contracts.

Component categories include

• Software (Dominating Segment)
• Hardware
• Services (Highest CAGR Segment)

Analysis by Device Type

Tabletop devices held the largest market share in 2025 because hospitals, ophthalmology clinics, and diagnostic centers continue to rely on tabletop fundus and OCT cameras for their higher image resolution, wider field of view, and established place in existing clinical workflows, and most of the earliest and most extensively validated AI clearances were built around these fixed cameras. Large diagnostic chains and tertiary hospitals, which account for a substantial share of total screening volume, continue to standardize on tabletop equipment for both diagnostic accuracy and existing capital investment reasons.

Handheld devices are projected to grow at the fastest CAGR during the forecast period. Battery-operated, handheld fundus cameras paired with offline or cloud AI software are enabling screening in primary care offices, pharmacies, and mobile outreach camps that cannot support a fixed tabletop camera, and recent regulatory clearances extending autonomous AI compatibility to handheld cameras are removing a major technical barrier to their wider clinical use. Falling hardware costs and improving image quality on portable cameras are together accelerating adoption of this device category across both high-income and resource-limited health systems.

Device Type categories include

• Tabletop Devices (Dominating Segment)
• Handheld Devices (Highest CAGR Segment)

Analysis by Application

Diabetic retinopathy screening held the largest market share in 2025 because diabetes remains the single largest driver of preventable vision loss worldwide, and diabetic retinopathy screening was the first indication to receive regulatory clearance and dedicated reimbursement codes in most major markets, giving it the longest track record of clinical use and payer acceptance. National screening programs built specifically around diabetic eye disease, such as those operated by health ministries and public insurers, continue to generate the largest recurring screening volumes for AI-enabled devices.

Age-related macular degeneration screening is projected to grow at the fastest CAGR during the forecast period. An aging global population, combined with the availability of effective anti-VEGF treatments that make early detection clinically actionable, is expanding demand for AI-based screening of age-related macular degeneration in both hospital and community settings. Developers are increasingly adding age-related macular degeneration modules to existing diabetic retinopathy platforms through a software update rather than new hardware, which is accelerating adoption of this application among providers that already operate a compatible screening device.

Application categories include

• Diabetic Retinopathy Screening (Dominating Segment)
• Age-Related Macular Degeneration Screening (Highest CAGR Segment)
• Glaucoma Screening
• Other Retinal Disease Screening

Analysis by End User

Hospitals held the largest market share in 2025 because hospitals maintain the largest installed base of tabletop retinal imaging equipment, host the highest daily patient volumes among diabetic and elderly populations, and are typically the first site to adopt a newly cleared AI system because of their existing capital budgets and specialist referral pathways. Multi-specialty hospitals that combine endocrinology and ophthalmology departments under one roof are particularly well positioned to run AI-based retinal screening as part of routine diabetes management visits.

Primary care and community health centers is projected to grow at the fastest CAGR during the forecast period. Regulatory clearances for autonomous, non-specialist-operated AI systems are allowing primary care physicians and community health workers to perform retinal screening as part of a routine diabetes check-up rather than referring every patient to a separate eye care appointment, closing a long-standing gap in annual screening compliance. Reimbursement codes that specifically cover point-of-care autonomous AI screening in primary care are reinforcing this shift and are expected to make this end-user segment the fastest growing through 2034.

End User categories include

• Hospitals (Dominating Segment)
• Primary Care and Community Health Centers (Highest CAGR Segment)
• Ophthalmology and Optometry Clinics
• Diagnostic and Imaging Centers

By Region

AI-Driven Retinal Screening Device Market Share, 2025

North America

45%

South America

xx%

Europe

xx%

Middle East Africa

xx%

Asia Pacific

24%

North America held the largest market share in 2025, supported by a dense base of FDA-cleared autonomous AI screening systems, broad reimbursement coverage under a dedicated Current Procedural Terminology code for point-of-care retinal AI screening, and high prevalence of diabetes and diabetic retinopathy across the United States. The United States accounts for the majority of regional demand, driven by adoption across primary care networks, federally qualified health centers, and Veterans Affairs eye care programs, while Canada is expanding AI-assisted screening through provincial diabetes management initiatives. Ongoing FDA clearances for handheld and multi-camera compatible AI systems, together with growing commercial and Medicare Advantage coverage of autonomous screening visits, continue to reinforce North America's leading position through the forecast period.

Asia Pacific is projected to grow at the fastest CAGR during the forecast period, driven by the region's very large diabetic populations in China and India, government-backed national eye screening programs, and the availability of low-cost, offline-capable portable screening devices developed specifically for high-volume, resource-limited deployment. China's regulator has granted Class III medical device approvals to multiple domestically developed AI screening platforms covering an expanding range of retinal diseases, while India's screening providers are scaling deployment across rural primary care and vision centers with support from state health departments. Rising healthcare investment, a growing base of domestic device manufacturers, and expanding public–private screening partnerships across Southeast Asia are expected to sustain Asia Pacific's lead in growth momentum through 2034.

Countries and Regions Covered

North America (Fastest to adopt, second-largest revenue growth)

• United States (Largest Country Market)
• Canada

Europe

• Germany (Largest Country Market)
• United Kingdom
• France
• Italy
• Spain
• Netherlands
• Rest of Europe

Asia Pacific (Dominating Growth Region)

• China (Largest Country Market)
• India (Fastest-Growing Country Market)
• Japan
• South Korea
• Australia
• Rest of Asia Pacific

Latin America

• Brazil (Largest Country Market)
• Mexico
• Argentina
• Rest of Latin America

Middle East & Africa

• Saudi Arabia (Largest Country Market)
• United Arab Emirates (Fastest-Growing Country Market)
• South Africa
• Rest of Middle East & Africa

Market Share

The AI-Driven Retinal Screening Device Market is fragmented, with a mix of established medical imaging companies, dedicated AI diagnostics startups, and regional device manufacturers competing across different price points and regulatory pathways. Companies such as Digital Diagnostics, Eyenuk, AEYE Health, and Topcon Healthcare have built leadership positions in North America and Europe on the strength of early FDA and CE clearances, while Airdoc, Remidio, and Forus Health lead large-volume deployment across Asia and other price-sensitive markets. Key success factors include regulatory clearance breadth, camera compatibility, reimbursement coverage, and clinical validation depth, prompting many companies to pursue distribution partnerships and targeted acquisitions, such as camera makers licensing third-party AI engines and software developers partnering with regional distributors, to expand geographic reach without building a full imaging hardware line of their own.

Key Players

• AEYE Health, Inc. (United States)
• Eyenuk, Inc. (United States)
• Digital Diagnostics Inc. (United States)
• Beijing Airdoc Technology Co., Ltd. (China)
• Mediwhale Inc. (South Korea)
• Forus Health Pvt. Ltd. (India)
• EyRIS Pte Ltd (Singapore)
• Remidio Innovative Solutions Pvt. Ltd. (India)
• Topcon Corporation (Japan)
• Revenio Group Corporation (Finland)
• Evolucare (France)
• RetinaLyze System A/S (Denmark)
• Retmarker S.A. (Portugal)
• Optomed Oy (Finland)

Recent Market Developments

• In July 2025, Topcon Healthcare acquired Intelligent Retinal Imaging Systems (IRIS), a cloud-based retinal screening technology company, and announced plans to integrate IRIS's referral and care-coordination capabilities into its Harmony connected-care platform, strengthening the link between primary care detection and downstream ophthalmology referral for diabetic eye disease.
• In August 2025, identifeye HEALTH launched its retinal screening platform, a compact, app-based system registered with the FDA under a 510(k)-exempt classification, and began pilot programs with health systems and community-based providers designed to let nurses and medical assistants capture retinal images with minimal training.
• In March 2026, Mediwhale closed a 20 billion Korean won Series C funding round to expand its Dr. Noon retina-based AI platform, which screens for cardiovascular, kidney, and eye disease risk, with proceeds directed toward clinical trials and regulatory submissions supporting United States market entry.
• In August 2026, Revenio Group confirmed that its iCare DRSplus fundus imaging system underpins an FDA-cleared autonomous AI solution developed by iHealthScreen for diabetic retinopathy screening in United States primary care settings, extending the commercial reach of Revenio's imaging hardware within a third-party AI diagnostic workflow.

Frequently Asked Questions

Key Questions Answered

Request a Sample

1

What is the AI-Driven Retinal Screening Device Market?

2

What is the CAGR of the AI-Driven Retinal Screening Device Market?

3

Which device type leads the AI-Driven Retinal Screening Device Market?

4

Which technology is growing the fastest in the AI-Driven Retinal Screening Device Market?

5

Which application dominates the AI-Driven Retinal Screening Device Market?

6

Which end user leads the AI-Driven Retinal Screening Device Market?

7

Which region leads the AI-Driven Retinal Screening Device Market?

Why Choose IG Transformation

Speak to Analyst

Strong Industry Focus

Extensive Product Offerings

Customer Research Services

Robust Research Methodology

Comprehensive Reports

Latest Technological Developments

Value Chain Analysis

Potential Market Opportunities

Growth Dynamics

Quality Assurance

Post-sales Support

Regular Report Updates