AI in Endoscopy Market By Component (Hardware, Software, Services), By Application (Gastrointestinal (GI) Endoscopy, Pulmonology Endoscopy, Urology Endoscopy, Gynecology Endoscopy, Orthopedic Endoscopy, Oncology Endoscopy, Others), By Technology (Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), Computer Vision, Big Data Analytics), By Functionality (Computer-aided Detection (CADe), Computer-aided Diagnosis (CADx), Workflow Optimization & Decision Support, Predictive Analytics & Prognosis), and By End User (Hospitals, Ambulatory Surgical Centers (ASCs), Specialty Clinics, Diagnostic & Imaging Centers, Research & Academic Institutes), Global Market Size, Segmental analysis, Regional Overview, Company share analysis, Leading Company Profiles And Market Forecast, 2025 – 2035

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What trends will shape AI in Endoscopy Market in the coming years?

The AI in Endoscopy Market accounted for USD 2.46 Billion in 2024 and USD 2.67 Billion in 2025 is expected to reach USD 6.06 Billion by 2035, growing at a CAGR of around 8.54% between 2025 and 2035. The AI in the endoscopy market is the application of artificial intelligence technology-based methods in endoscopic procedures, which improve diagnostic accuracy, efficiency, and decision-making. These AI systems help to identify abnormalities, such as polyps or lesions, and help with the early diagnosis of gastrointestinal diseases, and help to minimise human error. The driving forces of this market are increasing demand for minimally invasive procedures and the development of medical imaging. The technology has a particularly significant effect on gastroenterology, enhancing the work of colonoscopy, gastroscopy, and similar diagnostics. The market will continue to grow in size within both the developed and emerging healthcare systems as the rate of adoption grows.

What do industry experts say about the AI in Endoscopy market trends?

"AI in endoscopy has the potential to standardize detection and reduce operator variability. By assisting physicians in identifying subtle lesions, it enhances accuracy and improves patient outcomes."

• Dr. Prateek Sharma, Professor of Medicine, University of Kansas School of Medicine; President, American Society for Gastrointestinal Endoscopy (ASGE)

"Artificial intelligence is already demonstrating significant benefits in colorectal cancer screening. AI-assisted polyp detection improves adenoma detection rates, which directly translates into cancer prevention."

• Dr. Michael Wallace, Professor of Medicine, Mayo Clinic, Florida; Director of Digestive Diseases Interventional Endoscopy

Which segments and geographies does the report analyze?

What are the key drivers and challenges shaping the AI in Endoscopy market?

How does increasing demand for precision improve diagnostic accuracy significantly?

The increased need for medical diagnostics with higher accuracy contributed greatly to the quality of the AI applications in endoscopy, which resulted in the earlier and more confident diagnosis of the disease. AI tools that are precision-based help clinicians by processing complex imaging data with high sensitivity and specificity to decrease human error. Research released by the U.S. National Institutes of Health (NIH) found that AI algorithms in endoscopic imaging were able to detect early-stage gastrointestinal cancers with sensitivity scores far above that of traditional techniques (in the 85% range).

The National Cancer Institute (NCI) points out that an improvement in the accuracy of the diagnosis directly leads to an improvement in the treatment and a decrease in healthcare costs. Moreover, research carried out in advanced medical institutions such as the Mayo Clinic confirmed that AI endoscopy technology could decrease missed lesions by up to 30%, which indicates that precision requirements can be translated into clinical advantages. This coming together of technology and precise medicine is influencing the flourishing of AI in the endoscopy markets across the globe.

Does integration with robotics enhance procedural speed and patient safety outcomes?

Endoscopy robotics has greatly enhanced the speed of the procedure and patient safety, which is a major force behind the adoption of AI in endoscopy. Research published by such organisations as the National Institutes of Health (NIH) suggests that robotic-assisted endoscopic surgeries help to decrease the time of operations by improving accuracy and stability. To illustrate, robotic platforms allow the instruments to be controlled more precisely and reduce the number of mistakes and complications. Clinical trial data show that robotic endoscopy reduces the risk of perforation and bleeding through visualisation and manoeuvre of complex anatomical regions.

Robotics helps to minimise the physical effort of the operators, which leads to stable performance in the case of longer operations. These enhancements are compatible with the objectives that health authorities like the U.S. Food and Drug Administration (FDA) establish to improve patient safety and the effectiveness of the procedures. In general, the integration of robotics is a revolutionary move that will enhance the speed and safety of endoscopic interventions.

Is limited technical expertise restricting AI deployment in rural hospitals?

A shortage of technical skills is a major impediment to implementing AI in rural healthcare, particularly in such solutions as endoscopy. With rural areas all around the world, the World Health Organisation (WHO) claims that there are not enough trained healthcare professionals, which restricts them from using and maintaining AI technologies. The National Rural Health Association in the U.S. indicates that hospitals in rural areas are finding it hard to hire and maintain competent employees to work with AI-based gadgets.

Most of the rural healthcare workers do not have access to continuous training on new AI tools, and the lack of exposure in the course of education contributes to the gap. Moreover, the lack of uniform digital infrastructure, including interoperability of electronic health records (EHR), makes it difficult to integrate AI, because high-quality data is the basis of such systems. The untapped potential of AI as a means of enhancing diagnostic accuracy and efficiency in rural endoscopy would not be possible without addressing these technical and training issues.

Can emerging markets support scalable AI adoption through infrastructure development?

The potential of the emerging markets is high to help bring scalable AI applications to endoscopy by developing targeted infrastructure and digitalising healthcare. With initiatives like the India AI Mission, the Indian government has prioritised AI and is investing in infrastructure and skill development, especially in rural areas where 70% of the population lives with limited access to healthcare.

AI-based endoscopy can enhance the quality of diagnosis and deliver remote guidance, overcoming the shortage of specialists. Schools emphasise the use of AI in minimising the incidence of diagnosis errors in endoscopy. Moreover, better connectivity and data management systems are allowing seamless AI tools into clinics. As digital infrastructure expands and the government supports initiatives to increase AI literacy and access, new markets are developing the infrastructure to support AI in healthcare and deliver a higher quality of patient outcomes.

Are collaborations with med-tech firms fostering innovative AI-driven solutions?

The cooperation between medical technology developers and universities is hastening the emergence of AI-based services in the endoscopy industry, which improves the quality of the diagnoses and the effectiveness of the procedure. Studies conducted by the U.S. National Institutes of Health (NIH) point out that AI-guided endoscopy enhances the rates of adenoma detection by around 8-10 percentage points, which is essential in the early detection of cancer. There are currently many clinical trials sponsored by government health agencies, including those listed in ClinicalTrials.gov, that are attempting to combine AI algorithms to optimise the results of gastrointestinal endoscopy.

Such educational facilities as Johns Hopkins and Harvard Medical School are creating AI models that could analyse live endoscopy images to reduce human error and workflow. These collaborations rely on machine learning to detect the changes of the mucosa that go unnoticed by the human eye and demonstrate how AI innovation can lead to improved patient care and disease management in endoscopy.

What are the key market segments in the AI in Endoscopy industry?

Based on the Component, the AI in Endoscopy Market is classified into Hardware, Software, and Services. The biggest segment in the AI in endoscopy market is software. Such significance is explained by the fact that AI algorithms and machine learning models are especially important in endoscopic images and video analysis to provide precise diagnosis, abnormality detection, and support to the decision-making process.

Real-time image processing, increased visualisation, and automated reporting are among the concepts facilitated by software solutions to produce a better clinical outcome. The AI software directly pushes innovation and value creation in this market as opposed to hardware, which is a platform, and services, which support implementation.

Based on the application, the AI in Endoscopy Market is classified into Gastrointestinal (GI) Endoscopy, Pulmonology Endoscopy, Urology Endoscopy, Gynecology Endoscopy, Orthopedic Endoscopy, Oncology Endoscopy, and Others. Software is the largest part of AI in the endoscopy market. It is significant because of the essential part AI algorithms and machine learning models perform when analysing endoscopic images and videos to correctly detect an abnormality and provide relevant support.

The clinical outcomes can be enhanced with the help of software solutions that allow real-time image processing and improved visualisation, and automated reporting. The AI software directly leads to innovation and value creation in this market, unlike hardware, which is a platform, and services, which facilitate implementation.

Which regions are leading the AI in Endoscopy market, and why?

The North American AI in endoscopy market is dominant because it has developed healthcare systems, well-established leading industry players, and an adoption of emerging healthcare technologies. The area is characterised by large-scale capital investment in AI development and creation, and by positive government policies that facilitate digital health transformation.

The adoption of AI-assisted diagnostics among healthcare providers is supported by high awareness regarding the advantages of the technology, including higher accuracy and less time spent on the procedure. Furthermore, gastrointestinal disorders are very common in the region, and more effective and accurate endoscopic procedures are in demand.

Technologists' partnerships with healthcare facilities further streamline the advancement and integration of products. Governmental institutions such as the FDA have been increasingly accommodating of AI-based medical devices, allowing entry into the market at a faster pace. All these lead to the superiority of North America in this space.

The Asia Pacific AI in endoscopy market is expanding because it has a confluence of fast technological penetration, growth in healthcare expenditure, and the growing prevalence of gastrointestinal diseases. The first countries that have been in the lead include China, Japan, South Korea, and India due to the robust government sponsorship of AI integration in healthcare and robust R&D infrastructure.

The increasing need to be able to diagnose early and accurately, particularly in ageing populations, is another driver of using AI-powered endoscopic equipment. Further, collaborations between technology firms and healthcare providers are speeding up innovation and introducing products.

The region has a strategic edge based on competitive pricing, the growth of medical tourism, and high patient volumes. Moreover, local production power and expedited regulatory clearance help in achieving faster penetration as opposed to the West. Overall, the combination of innovations, demand, and infrastructure in the region contributes to the region being a leader in this industry globally

What does the competitive landscape of the AI in Endoscopy market look like?

The endoscopy AI market is undergoing fast development due to the latest achievements in the technology of deep learning and computer vision that increase the precision and effectiveness of diagnostics during gastrointestinal practices. The major players like Medtronic plc, Olympus Corporation, Fujifilm Holdings, and Hoya Corporation have been in the fray, incorporating AI algorithms to help in real-time polyp detection and characterisation.

Other innovative AI platforms, such as Odin Medical Ltd and Iterative Health, are also gaining momentum in their startups to enhance clinical outcomes. Some of the latest trends include strategic partnerships between experienced firms with AI experts to expedite product commercialisation and regulatory licensing.

As an example, Olympus has recently invested in AI capabilities by collaborating with technology software companies, and Medtronic invested in AI-driven solutions to add to its portfolio of endoscopies. The competitive environment represents a combination of long-established medical device leaders and nimble startups, all geared towards the use of AI to end with shorter procedure times and improved early disease detection.

AI in Endoscopy Market, Company Shares Analysis, 2024

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Which recent mergers, acquisitions, or product launches are shaping the AI in Endoscopy industry?

• In June 2025, AI Medical Service Inc. (AIM) received regulatory approval from Thailand’s FDA for its gastroAI-model G, an AI-based system designed to help differentiate between neoplastic and non-neoplastic gastric lesions during upper GI endoscopy.
• In March 2025, Intelliscopes announced a strategic alliance with Integrated Endoscopy. The partnership combined Intelliscopes’ AI-enhanced endoscopy tools with Integrated Endoscopy’s wireless arthroscopy platform to improve surgical workflows and visualization.

Report Coverage:

By Component

• Hardware
• Software
• Services

By Application

• Gastrointestinal (GI) Endoscopy
• Pulmonology Endoscopy
• Urology Endoscopy
• Gynecology Endoscopy
• Orthopedic Endoscopy
• Oncology Endoscopy
• Others

By Technology

• Machine Learning (ML)
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Big Data Analytics

By Functionality

• Computer-aided Detection (CADe)
• Computer-aided Diagnosis (CADx)
• Workflow Optimization & Decision Support
• Predictive Analytics & Prognosis

By End User

• Hospitals
• Ambulatory Surgical Centers (ASCs)
• Specialty Clinics
• Diagnostic & Imaging Centers
• Research & Academic Institutes

By Region

North America

• U.S.
• Canada

Europe

• U.K.
• France
• Germany
• Italy
• Spain
• Rest of Europe

Asia Pacific

• China
• Japan
• India
• Australia
• South Korea
• Singapore
• Rest of Asia Pacific

Latin America

• Brazil
• Argentina
• Mexico
• Rest of Latin America

Middle East & Africa

• GCC Countries
• South Africa
• Rest of Middle East & Africa

List of Companies:

• Medtronic plc
• Olympus Corporation
• Fujifilm Holdings Corporation
• Hoya Corporation
• Pentax Corporation
• NEC Corporation
• Magentiq Eye Ltd.
• Odin Medical Ltd.
• Wuhan EndoAngel Medical Technology Company
• Iterative Health Inc.
• Wision A.I.
• CapsoVision
• Boston Scientific Corporation
• Cosmo Pharmaceuticals
• Insign Medical Technologies

Frequently Asked Questions (FAQs)