U.S. AI-Enabled Gastroenterology Devices Market $7.35B 2035

Market Outlook

By 2035, the U.S. AI-Enabled Gastroenterology Devices Market is projected to reach approximately USD 7.35 billion, expanding at a CAGR of 19.10% during the forecast period 2026–2035. The market is estimated at USD 1.28 billion in 2025, with historical analysis covering 2021–2024. Values in this report are expressed in USD billions.

The U.S. AI-enabled gastroenterology devices industry is moving from an early-adoption technology category toward an increasingly important layer of the gastrointestinal diagnostic and procedural ecosystem. Artificial intelligence is being integrated into colonoscopy, upper gastrointestinal endoscopy, capsule endoscopy, image interpretation, lesion detection, optical characterization, inflammatory disease assessment, procedural quality monitoring, and connected gastroenterology workflows. The commercial opportunity is therefore broader than standalone AI software. It increasingly includes AI-compatible processors, imaging platforms, intelligent endoscopy modules, cloud-connected systems, advanced visualization technologies, and diagnostic devices whose value proposition depends partly on machine-learning-enabled clinical support.

The underlying procedure base is substantial. More than 20 million gastrointestinal endoscopic procedures are estimated to be performed annually in the United States. Colonoscopy represents one of the largest addressable workflows because of its central role in colorectal cancer screening, surveillance, polypectomy, inflammatory bowel disease assessment, and diagnostic evaluation. In 2025, an estimated 154,270 new colorectal cancer cases were expected in the United States, with approximately 52,900 deaths. Screening recommendations beginning at age 45 for average-risk adults have also expanded the eligible population for colorectal cancer screening, increasing the long-term strategic value of technologies capable of improving examination quality and lesion detection.

AI adoption accelerated after the U.S. regulatory pathway became clearer. The first FDA-authorized artificial-intelligence system designed to assist detection of colorectal lesions during colonoscopy entered the U.S. market in 2021. Since then, additional computer-aided detection platforms have received regulatory clearance, creating a competitive market rather than a single-product category. By 2024–2025, the U.S. market had expanded to include multiple AI-assisted colonoscopy solutions, hardware-integrated systems and cloud-delivered architectures.

The historical market is estimated to have increased from approximately USD 0.43 billion in 2021 to USD 0.99 billion in 2024. Growth during this period was unusually rapid because the market began from a limited installed base and benefited from new FDA clearances, clinical evidence generation, post-pandemic recovery in elective endoscopy volumes, increasing colorectal cancer screening activity, and investment by gastroenterology groups and ambulatory endoscopy centers in procedural quality technologies. The market reached an estimated USD 1.28 billion in 2025 as AI increasingly became part of capital equipment discussions, endoscopy-suite upgrades and enterprise gastroenterology technology strategies.

From 2026 through 2035, growth will increasingly be driven by a transition from simple computer-aided polyp detection toward broader intelligent gastroenterology platforms. These systems are expected to support detection, characterization, disease scoring, quality assurance, procedural documentation, image management, predictive analytics and eventually more personalized therapeutic decision support. The most commercially successful technologies will be those that improve clinical performance while remaining sufficiently unobtrusive to preserve endoscopy-suite throughput.

Introduction

According to the U.S. AI-Enabled Gastroenterology Devices Market Report, artificial intelligence is becoming a strategically important technology layer within U.S. gastroenterology because the specialty combines extremely high imaging volumes, operator-dependent interpretation, repetitive visual assessment, quality-measure requirements and a substantial burden of preventable gastrointestinal disease.

Gastroenterology is particularly well suited to AI-assisted medical devices. Colonoscopy and upper GI endoscopy generate continuous video containing thousands of images during every examination. Physicians must identify lesions while simultaneously controlling the scope, assessing mucosal exposure, determining whether abnormalities require intervention, documenting findings and maintaining procedure efficiency. AI can provide a persistent second-observer function without fundamentally changing the procedure itself.

The clinical opportunity is significant because colonoscopy performance varies between operators. Adenomas may be difficult to identify when they are small, flat, located behind mucosal folds, incompletely exposed or visually subtle. Sessile serrated lesions can be particularly challenging because of their morphology. Artificial intelligence systems designed for computer-aided detection can analyze endoscopic video in real time and highlight areas that may require closer physician inspection.

The market is also extending beyond colorectal polyp detection. Developers are applying AI to Barrett’s esophagus, esophageal neoplasia, gastric lesions, inflammatory bowel disease severity, ulcerative colitis scoring, gastrointestinal bleeding, capsule endoscopy interpretation, bowel preparation assessment, anatomical landmark recognition and endoscopy quality measurement. These applications expand the addressable market from screening colonoscopy into the broader GI diagnostic continuum.

The economic structure of U.S. endoscopy creates both opportunity and adoption friction. High-volume ambulatory surgery centers may conduct dozens of procedures per room each day, meaning even minor workflow delays can materially affect facility economics. Hospitals and physician-owned endoscopy centers therefore evaluate AI according to its impact on detection quality, physician consistency, procedure duration, pathology utilization, staff workload, equipment compatibility, subscription cost and long-term quality metrics.

A distinguishing characteristic of this market is that reimbursement for the underlying procedure is well established, while AI often must be economically justified within existing procedural economics rather than relying on a separate AI-specific payment stream. Vendors therefore need to prove that AI creates value through improved examination quality, differentiation of the endoscopy center, risk reduction, clinical standardization, physician recruitment, operational efficiency or downstream disease prevention.

Over the forecast period, AI is expected to become increasingly integrated directly into endoscopy processors, cloud platforms and enterprise imaging environments. This transition will shift competitive advantage away from isolated algorithms toward vendors capable of controlling or connecting the entire procedural ecosystem.

Key Market Drivers: What’s Fueling the U.S. AI-Enabled Gastroenterology Devices Market Boom?

The first major driver is the scale of gastrointestinal diagnostic activity in the United States. More than 20 million GI endoscopies are performed annually, providing an exceptionally large stream of visual data and recurring procedures where artificial intelligence can be deployed. Unlike technologies limited to rare diseases or highly specialized procedures, AI-enhanced endoscopy can potentially be used across routine screening, surveillance and diagnostic examinations.

Colorectal cancer prevention is the most important near-term commercial driver. Approximately 154,270 new colorectal cancers were expected in the United States in 2025, and colorectal cancer remains a major cause of cancer mortality. Because many colorectal cancers develop through identifiable precursor lesions, technologies capable of helping physicians detect additional adenomas or serrated lesions have a direct connection to established prevention pathways. The expansion of routine screening to adults beginning at age 45 has increased the addressable screening population and strengthens the long-duration procedure outlook.

A second driver is growing emphasis on measurable colonoscopy quality. Gastroenterology practices increasingly compete on clinical performance, patient experience, procedural capacity and payer relationships. Adenoma detection, cecal intubation, withdrawal quality, bowel preparation and appropriate surveillance recommendations are all relevant performance dimensions. AI technologies capable of making these measurements more objective can evolve from optional diagnostic enhancements into quality-management infrastructure.

A third driver is physician workload. Artificial intelligence is particularly valuable where clinicians perform repetitive image-intensive tasks over long procedure schedules. Detection performance can be affected by distraction, fatigue and differences in experience. AI does not eliminate physician responsibility, but a continuously operating digital observer can provide greater consistency across high-volume lists and across clinicians with different experience levels.

A fourth driver is the continued migration of gastroenterology procedures toward ambulatory environments. Freestanding endoscopy centers and ambulatory surgery centers are economically important purchasers because colonoscopy and upper GI endoscopy are well suited to outpatient care. These facilities prioritize technologies that are compact, interoperable, fast to deploy and economically scalable across multiple rooms. Subscription-based or cloud-delivered AI can be particularly attractive when it reduces the need for dedicated onsite computing infrastructure.

Hospital consolidation and gastroenterology practice aggregation are also accelerating adoption. Large GI physician groups and integrated delivery networks can evaluate AI across hundreds of physicians and multiple endoscopy sites. Enterprise contracting creates a commercial pathway for vendors to scale much faster than through individual physician sales. It also raises competitive barriers because health systems increasingly expect cybersecurity support, fleet management, analytics, centralized software updates and integration with existing endoscopic equipment.

Another major driver is the improving regulatory maturity of AI-enabled colonoscopy. The U.S. market has progressed from a single pioneering system to multiple FDA-cleared solutions. Medtronic/Cosmo’s GI Genius, Iterative Health’s SKOUT, Fujifilm’s CAD EYE and Olympus/Odin’s CADDIE illustrate the diversification of the commercial landscape. This expansion reduces the perception that AI-assisted colonoscopy is experimental and forces buyers to compare competing architectures, clinical evidence and total ownership costs.

The final major driver is platform expansion. The strongest long-term opportunity is not simply identifying colorectal polyps. AI applications are being developed for optical diagnosis, Barrett’s esophagus, inflammatory bowel disease, upper GI lesions, capsule endoscopy, bowel preparation, anatomical landmarks, procedure quality and clinical workflow. Every additional validated indication improves the economic justification for installing an AI-capable ecosystem.

Innovation in Focus: How Manufacturers Are Raising the Bar?

Innovation in AI-enabled gastroenterology is moving through several distinct generations. The first generation focused primarily on computer-aided detection, where algorithms identify a possible lesion and generate a visual marker or alert for the physician. This remains the largest commercial AI application because it fits naturally into existing colonoscopy workflows and addresses a highly measurable clinical endpoint.

The next innovation cycle is computer-aided diagnosis and characterization. Instead of merely identifying a suspected lesion, future systems increasingly aim to support assessment of lesion type, neoplastic potential or management pathway. This could influence whether diminutive lesions are removed, sampled, surveilled or otherwise managed. Regulatory requirements will be more demanding because characterization affects clinical decisions more directly than detection.

Cloud architecture represents another major shift. Traditional AI modules require local computing hardware connected to the endoscopy tower. Cloud-based platforms can potentially centralize software management, accelerate algorithm updates, facilitate multi-site deployment and reduce hardware complexity. Olympus’ commercialization strategy around cloud-connected intelligent endoscopy illustrates how future competition may center on the software ecosystem surrounding the endoscope rather than the processor alone.

Manufacturers are also developing AI-based procedural quality tools. Future systems can potentially identify the cecum, assess bowel preparation, estimate withdrawal quality, quantify visible mucosa, measure inspection patterns and automatically organize procedure metadata. This is strategically significant because health systems may find enterprise quality analytics easier to justify economically than a single detection algorithm.

Inflammatory bowel disease represents an important emerging application. Ulcerative colitis and Crohn’s disease require repeated endoscopic evaluation, and visual assessment can vary between clinicians. AI-supported scoring has the potential to standardize disease severity assessment, improve clinical trial measurements and support more reproducible treatment decisions.

Upper GI applications are another major innovation frontier. Algorithms are being developed to identify suspicious changes associated with Barrett’s esophagus, dysplasia, esophageal cancer and gastric neoplasia. U.S. penetration is currently less mature than colorectal CADe, but the opportunity is strategically attractive because the same AI-enabled endoscopy ecosystem can potentially support multiple applications.

Capsule endoscopy is especially suitable for artificial intelligence because clinicians may need to review extremely large numbers of images produced during a single examination. AI can prioritize suspicious frames, identify bleeding, ulcers or other abnormalities and reduce interpretation burden. Over time, AI-assisted capsule review could improve the economics of small-bowel diagnostic pathways by reducing physician reading time while increasing consistency.

Artificial intelligence is also beginning to converge with endoscopic ultrasound and pancreaticobiliary imaging. Advanced pattern recognition may eventually assist lesion identification, tissue characterization and procedural planning in technically demanding areas such as pancreatic disease. Commercial adoption will be slower than routine colonoscopy because procedure volumes are smaller and regulatory requirements can be more complex, but average economic value per procedure is higher.

Ultimately, innovation is moving toward a closed-loop intelligent endoscopy environment in which the system can help identify lesions, assess examination quality, organize images, populate documentation, support treatment decisions and contribute to longitudinal patient records. Vendors controlling several layers of this workflow will have a strategic advantage over single-algorithm companies.

Segmentation Insights

The U.S. AI-Enabled Gastroenterology Devices Market is segmented on the basis of product category, AI functionality, clinical application, end user and geography.

By Product Category

AI-Enabled Endoscopy and Colonoscopy Systems

AI-enabled endoscopy and colonoscopy systems represent the largest product category in 2025. The segment includes computer-aided polyp detection modules, integrated AI processors, intelligent endoscopy towers, cloud-connected detection systems and compatible visualization platforms. Colonoscopy is the primary commercial entry point because of the high procedure volume, established quality measures and direct relationship between adenoma detection and colorectal cancer prevention.

This segment is transitioning from add-on modules toward integrated architectures. Large manufacturers are increasingly embedding AI compatibility into next-generation endoscopy ecosystems, creating opportunities to link scopes, processors, software and cloud services under a single commercial platform. High-volume endoscopy centers are likely to favor systems that can be deployed without materially increasing procedure time or staff complexity.

AI-Enabled Capsule Endoscopy Systems

AI-enabled capsule endoscopy is a smaller but high-growth product category. Capsule examinations generate thousands of images, making automated image prioritization particularly valuable. Artificial intelligence can support detection of bleeding, vascular abnormalities, inflammatory lesions, ulcers and small-bowel pathology while reducing manual reading requirements.

The segment is attractive for U.S. providers because greater reading efficiency could improve physician productivity and expand capsule utilization. Long-term growth will depend on diagnostic accuracy, reimbursement economics, interoperability with reporting systems and evidence showing that AI-assisted interpretation can maintain clinical sensitivity while reducing review time.

AI-Assisted Endoscopic Ultrasound and Advanced GI Imaging Systems

AI-assisted EUS and advanced imaging represent an emerging premium category. These systems are relevant to pancreatic lesions, biliary disease, subepithelial abnormalities and other complex GI conditions requiring advanced image interpretation. Academic medical centers and high-volume referral hospitals are likely to lead adoption because they have the specialist expertise and case volumes required to justify premium technology.

Commercial expansion will be slower than colorectal CADe, but the category offers substantial long-term value because advanced imaging procedures are clinically complex and economically important.

AI-Integrated GI Diagnostic and Monitoring Devices

This category includes intelligent gastrointestinal diagnostic systems that combine physiologic data, imaging, connected sensors or algorithmic interpretation. Applications can include GI motility assessment, functional disease evaluation, reflux monitoring and other data-intensive diagnostic pathways.

Growth will depend on whether AI produces clinically actionable improvements rather than merely additional data. Products that simplify interpretation, reduce manual analysis or identify patterns associated with treatment response will have stronger commercial potential.

AI-Enabled Procedural Quality and Connected GI Device Platforms

AI-enabled quality and workflow platforms form an increasingly strategic category. These technologies analyze procedural information to support quality measurement, anatomical landmark recognition, mucosal visualization assessment, image capture and standardized reporting.

Although some solutions generate lower per-procedure revenue than premium hardware, recurring software economics and enterprise deployment can create attractive lifetime value. These platforms may eventually become a major bridge between medical devices, electronic health records and gastroenterology analytics.

By AI Functionality

Computer-Aided Detection

Computer-aided detection currently accounts for the largest share of AI-enabled gastroenterology device revenue. CADe platforms evaluate live endoscopic video and highlight areas that may contain lesions. Colorectal polyp and adenoma detection is the most commercially developed application.

Growth is supported by straightforward workflow integration and an easily understood physician value proposition: an additional continuously operating observer that can draw attention to subtle abnormalities.

Computer-Aided Diagnosis and Lesion Characterization

CADx represents the next major value layer. These algorithms aim to characterize lesions after detection and assist physicians in determining their clinical significance. Successful commercialization could reduce unnecessary intervention, improve consistency and support more personalized management strategies.

CADx carries a higher regulatory and evidence burden because incorrect characterization can influence treatment. For this reason, U.S. adoption is expected to follow CADe rather than replace it.

Procedural Quality and Completeness Assessment

Quality-assessment algorithms analyze whether an endoscopic examination was conducted thoroughly. Potential functions include withdrawal assessment, cecal landmark recognition, bowel preparation evaluation and measurement of mucosal exposure.

This segment could gain significant enterprise demand because it addresses gastroenterology practice management as well as individual physician performance.

Disease Severity and Quantitative Scoring

AI-based disease scoring is particularly relevant for inflammatory bowel disease and Barrett’s esophagus. Algorithms can potentially standardize visual assessment and reduce inter-observer variability.

The technology is attractive to academic centers, pharmaceutical trial networks and specialty GI practices because objective scoring may improve treatment monitoring and evidence generation.

Predictive and Clinical Decision Support

Predictive AI remains an emerging segment. Future applications may combine endoscopic findings with patient history, pathology, laboratory information and longitudinal outcomes to estimate progression risk or recommend surveillance pathways.

This segment could ultimately generate substantial clinical value, but adoption will depend heavily on regulatory validation, explainability, integration and physician confidence.

By Clinical Application

Colorectal Cancer Screening and Polyp Detection

Colorectal cancer screening is the dominant clinical application and is expected to remain the largest segment through much of the forecast period. The combination of high procedure volume, established screening recommendations, measurable quality metrics and FDA-cleared products creates a favorable commercial environment.

AI-assisted colonoscopy is increasingly moving from technology demonstration toward routine procurement consideration, particularly among large gastroenterology groups and high-volume ASCs.

Barrett’s Esophagus and Upper GI Neoplasia

Barrett’s esophagus surveillance is an important emerging opportunity because dysplastic changes can be difficult to identify and may require expert interpretation. Artificial intelligence could help identify suspicious areas requiring biopsy or treatment.

Upper GI AI adoption will initially concentrate at tertiary medical centers and specialist practices before expanding into broader community settings.

Inflammatory Bowel Disease

IBD applications include ulcerative colitis severity assessment, mucosal healing evaluation and disease monitoring. Objective AI-supported scoring could improve consistency across physicians and sites.

Demand will be particularly strong where gastroenterology practices manage large biologic-treated populations and need reliable longitudinal disease assessment.

GI Bleeding and Small-Bowel Disease

Capsule endoscopy and related imaging technologies create a natural opportunity for AI because small-bowel examinations can generate a large image-reading workload. Automated identification of bleeding, vascular lesions, ulcers and inflammatory abnormalities can potentially improve reading efficiency.

The value proposition is centered as much on physician productivity as on diagnostic sensitivity.

Pancreaticobiliary and Advanced Endoscopic Imaging

Pancreatic and biliary disease represents a smaller but clinically valuable AI application. Advanced endoscopic ultrasound, cholangioscopy and other complex imaging procedures can potentially benefit from AI-assisted lesion identification and characterization.

Academic medical centers will remain the principal early adopters, followed by large regional referral systems.

By End User

Hospitals and Integrated Health Systems

Hospitals and integrated delivery networks represent the largest end-user category by value because they purchase premium endoscopy platforms, advanced imaging systems and enterprise software. Large organizations increasingly evaluate AI through multidisciplinary value-analysis processes involving gastroenterologists, IT departments, cybersecurity teams, procurement leaders and finance executives.

Enterprise interoperability, software support and clinical evidence are particularly important in this segment.

Ambulatory Surgery Centers and Endoscopy Centers

ASCs and dedicated endoscopy centers represent one of the fastest-growing customer groups. These facilities conduct high procedure volumes and therefore have strong incentives to standardize colonoscopy quality while maintaining rapid room turnover.

AI platforms that are easy to install, compatible with existing towers and economically scalable across multiple procedure rooms are positioned favorably.

Gastroenterology Physician Practices

Large gastroenterology groups are becoming increasingly influential purchasers, particularly as practice consolidation creates regional and national networks. AI can support quality consistency across physicians, strengthen patient-facing differentiation and provide centralized performance analytics.

Vendor success in this segment increasingly depends on enterprise contracting rather than conventional one-device-at-a-time selling.

Academic Medical Centers and Specialty GI Institutes

Academic institutions remain strategically important because they conduct clinical trials, develop AI validation datasets, evaluate emerging indications and train physicians. These centers are likely to lead adoption in Barrett’s esophagus, inflammatory bowel disease, EUS and other advanced applications.

Their direct revenue contribution may be smaller than large community networks, but their influence on national clinical adoption is disproportionately high.

Diagnostic and Multispecialty Care Networks

Multispecialty centers, advanced diagnostic organizations and integrated outpatient networks represent an emerging end-user segment as GI care becomes more connected. These organizations may use AI-enabled imaging, capsule technologies and diagnostic systems as part of broader coordinated care pathways.

Regional Insights: Where the Market is Growing Fastest

The U.S. AI-Enabled Gastroenterology Devices Market is geographically segmented into the South, West, Northeast and Midwest. Regional performance differs according to population scale, colorectal cancer screening volumes, gastroenterologist density, ASC penetration, hospital capital spending, academic research activity, payer structure, availability of advanced endoscopy and willingness of provider organizations to invest in digital clinical infrastructure.

The South is estimated to represent the largest regional market in 2025 at approximately USD 0.40 billion, while the West is expected to record the fastest growth through 2035. The Northeast remains highly important for clinical validation and premium academic adoption, while the Midwest provides a large base of integrated health systems and established gastroenterology networks.

South

The South represents the largest regional opportunity because it combines rapid population growth, a substantial older-adult population, significant colorectal cancer burden and a large network of hospitals, physician-owned GI practices and ambulatory endoscopy centers. The regional market is estimated at approximately USD 0.40 billion in 2025 and could exceed USD 2.25 billion by 2035.

The region includes Texas, Florida, Georgia, North Carolina, South Carolina, Virginia, West Virginia, Maryland, Delaware, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana and Oklahoma, together with the District of Columbia within broader commercial territory planning.

Texas is one of the largest individual state opportunities. Houston, Dallas-Fort Worth, Austin and San Antonio contain extensive academic and private GI networks, large integrated health systems and substantial outpatient procedure infrastructure. Scale makes Texas particularly attractive for enterprise deployments in which an AI vendor can contract across multiple endoscopy centers.

Florida is similarly important because of its large Medicare-age population and high volume of gastrointestinal screening and surveillance. AI-assisted colonoscopy is commercially well suited to the state’s extensive ambulatory endoscopy ecosystem, where procedural quality must be balanced against high throughput.

North Carolina has a strong combination of academic medicine, regional health systems and fast-growing metropolitan populations. Charlotte, Raleigh-Durham and other markets support sophisticated gastroenterology networks capable of adopting cloud-based and connected AI platforms.

Georgia, Tennessee and Virginia are also attractive growth markets because of major urban referral centers and expansion of physician practice networks. Atlanta, Nashville, Richmond and Northern Virginia are likely to remain important commercial centers for advanced endoscopy investment.

Alabama, Mississippi, Louisiana, Arkansas, Kentucky, West Virginia and Oklahoma have important unmet needs associated with colorectal cancer burden, rural access and specialist availability. AI cannot solve provider shortages, but technologies that improve examination consistency or enable centralized quality oversight may be particularly valuable in networks serving geographically dispersed populations.

The South is expected to maintain regional leadership through 2035 because absolute procedure volume will continue rising. Competition will increasingly shift from selling individual AI boxes to securing enterprise agreements with GI groups, health systems and ASC operators.

West

The West is estimated at approximately USD 0.35 billion in 2025 and is expected to become nearly as large as the South by 2035, potentially reaching around USD 2.23 billion. Its above-market growth is supported by high digital-health adoption, strong venture funding, sophisticated integrated health systems and a large technology-development ecosystem.

The region includes California, Washington, Oregon, Arizona, Nevada, Colorado, Utah, New Mexico, Idaho, Montana, Wyoming, Alaska and Hawaii.

California is the dominant Western state and one of the most strategically important AI-enabled gastroenterology markets nationally. The state combines a large population with major academic medical centers, large integrated delivery networks, high technology acceptance and extensive digital health activity. California providers are particularly attractive launch partners for cloud AI, connected endoscopy, advanced imaging and multi-application AI platforms.

The Bay Area, Los Angeles, San Diego and other metropolitan markets have sophisticated provider organizations capable of performing detailed technology assessments. Vendors entering California must therefore offer strong clinical evidence and cybersecurity capabilities, but successful adoption can create important reference accounts.

Arizona and Nevada are high-growth markets because of population expansion and aging demographics. Phoenix, Tucson and Las Vegas continue to add outpatient specialty infrastructure, supporting demand for colonoscopy, cancer screening and advanced GI diagnostics.

Washington and Oregon have mature integrated health systems and a relatively strong orientation toward digital care models. Their provider environments are well suited to enterprise software, centralized quality analytics and cloud-enabled endoscopy applications.

Colorado and Utah are smaller but innovation-oriented markets with strong health systems and research capabilities. Denver and Salt Lake City serve as regional referral hubs for surrounding states and can influence technology adoption across broader Western territories.

New Mexico, Idaho, Montana, Wyoming, Alaska and Hawaii represent smaller revenue pools but important access markets. AI-enabled platforms capable of supporting standardized quality across distributed networks could become increasingly valuable as these states balance rural access limitations with regionalized specialist care.

The West is likely to gain market share because the future of AI-enabled GI devices will increasingly involve cloud infrastructure, connected data, multi-site analytics and software-led upgrade cycles—areas where Western health systems have historically demonstrated strong adoption capacity.

Northeast

The Northeast is estimated to account for approximately USD 0.31 billion in 2025 and could reach around USD 1.72 billion by 2035. Although the region is smaller by population than the South, it has one of the country’s highest concentrations of academic hospitals, gastroenterology specialists, clinical researchers and complex-care centers.

The region includes New York, Pennsylvania, New Jersey, Massachusetts, Connecticut, Rhode Island, Vermont, New Hampshire and Maine.

New York is the largest market in the Northeast. New York City contains a dense network of tertiary hospitals, academic centers and specialty gastroenterology practices capable of evaluating sophisticated AI technologies. Upstate health systems provide an additional opportunity for centralized AI deployment across geographically distributed facilities.

Pennsylvania is another major market, with Philadelphia and Pittsburgh serving as important academic and regional referral centers. The state’s mix of health-system-owned facilities and community gastroenterology creates opportunities across both premium and standardized deployment models.

Massachusetts has disproportionate strategic influence because of its concentration of academic medicine, biotechnology, medical-device development and AI research. Boston-based clinical centers frequently participate in technology validation and can influence national adoption patterns even when local procedure volumes are lower than those of larger states.

New Jersey and Connecticut benefit from high physician density, substantial commercially insured populations and proximity to major Northeast medical markets. They are attractive for advanced outpatient GI services and premium equipment adoption.

Maine, Vermont, New Hampshire and Rhode Island are smaller markets but can support regional health-system deployments, particularly where AI provides standardized quality across community sites.

The Northeast will remain one of the most evidence-sensitive markets. Procurement committees are likely to demand rigorous clinical validation, cybersecurity documentation, health-economic justification and integration planning. For AI companies, successful penetration of leading Northeast institutions can provide reputational advantages that extend nationally.

Midwest

The Midwest represented an estimated USD 0.22 billion in 2025 and could reach approximately USD 1.15 billion by 2035. Growth is expected to be steady rather than speculative, supported by large health systems, established gastroenterology programs, high colorectal screening demand and strong regional referral networks.

The region includes Illinois, Ohio, Michigan, Indiana, Wisconsin, Minnesota, Missouri, Iowa, Kansas, Nebraska, North Dakota and South Dakota.

Illinois is the largest AI-enabled GI market in the Midwest. Chicago has an extensive network of academic institutions, large health systems, community hospitals and specialty gastroenterology practices. These organizations provide a diverse customer base for both premium AI platforms and cost-conscious enterprise deployments.

Ohio is particularly important because of its high concentration of major health systems and specialist care networks. Cleveland, Columbus and Cincinnati support substantial endoscopy volumes and strong clinical infrastructure.

Michigan has a large hospital and GI practice base centered on Detroit and other population centers. Opportunities are strongest for technologies that can demonstrate measurable procedural-quality improvements across multi-hospital systems.

Minnesota has strategic relevance beyond population size because of its established medical-technology ecosystem and sophisticated integrated health providers. The state is well positioned for clinical evaluation of connected gastroenterology devices and advanced imaging technologies.

Indiana, Wisconsin and Missouri provide substantial community and regional procedure volumes. Iowa, Kansas and Nebraska offer smaller but durable markets where health systems often serve extensive geographic catchment areas.

North Dakota and South Dakota have limited absolute market size but illustrate an important future use case for AI: supporting consistent clinical quality across regional referral networks serving dispersed populations.

The Midwest is expected to remain highly attractive to vendors with strong service organizations and flexible contracting. Health systems in the region often emphasize measurable operating value, interoperability and long-term vendor reliability, which may favor established medtech companies and well-capitalized AI specialists.

Key Market Players

The U.S. AI-Enabled Gastroenterology Devices Competitive Landscape is evolving from a startup-led innovation market into a platform competition involving multinational endoscopy manufacturers, gastrointestinal device companies, specialized AI developers, capsule-endoscopy companies and digital pathology or imaging organizations.

Large medtech manufacturers have structural advantages because they already control endoscopy towers, scopes, processors, service contracts and purchasing relationships. Specialized AI companies remain important because they can innovate rapidly, develop vendor-agnostic architectures and focus on narrower clinical problems.

Some of the key companies and strategically relevant participants in the U.S. AI-enabled gastroenterology device ecosystem include:

Medtronic
Cosmo Pharmaceuticals N.V. / Cosmo Intelligent Medical Devices
Olympus Corporation
Odin Medical Ltd. / Odin Vision
FUJIFILM Healthcare Americas Corporation
Iterative Health
PENTAX Medical
Wision A.I.
Magentiq Eye
NEC Corporation
AnX Robotica
CapsoVision
Virgo Surgical Video Solutions
Satisfai Health
EndoSound
CDx Diagnostics
PathAI
Ibex Medical Analytics
Proscia
Paige
GE HealthCare
Siemens Healthineers
Philips
Ambu A/S
SonoScape Medical

Medtronic and Cosmo have an important first-mover position through the GI Genius ecosystem. Fujifilm has strengthened competition by integrating AI functionality into its endoscopy architecture, while Olympus is pursuing a broader intelligent-endoscopy strategy that combines conventional endoscopy leadership with cloud-delivered AI.

Iterative Health represents the specialist AI model, focusing deeply on gastroenterology and creating products around colonoscopy detection and broader data-driven GI workflows. Companies such as Wision A.I. and Magentiq Eye increase competitive pressure by developing focused computer-vision capabilities.

Capsule-endoscopy companies such as AnX Robotica and CapsoVision participate in another high-potential AI pathway because automated image review can materially change physician workflow economics.

Over time, competitive advantage will depend on more than algorithm accuracy. Buyers will evaluate interoperability, latency, false-alert burden, cybersecurity, regulatory durability, software-update processes, fleet management, clinical evidence, physician acceptance and enterprise pricing.

The market is therefore expected to consolidate around two viable competitive models: broad endoscopy ecosystems capable of bundling AI into capital equipment relationships, and highly differentiated specialist AI vendors capable of demonstrating superior performance or vendor-neutral integration.

Recent Developments

Recent developments in the U.S. AI-Enabled Gastroenterology Devices Market show that the category has moved beyond a single pioneering product and into a broader competitive cycle.

The FDA authorization of GI Genius in 2021 established the first major U.S. regulatory pathway for real-time AI-assisted colorectal lesion detection. The product demonstrated that artificial intelligence could be positioned as an adjunct to the gastroenterologist rather than an autonomous diagnostic replacement.

Iterative Health subsequently expanded competition through SKOUT, adding another FDA-cleared real-time computer-aided polyp detection platform. This development was strategically important because competition began shifting toward comparative clinical performance, workflow fit and commercial model rather than simply whether AI could be used during colonoscopy.

In 2024, Fujifilm received U.S. clearance for CAD EYE, integrating artificial-intelligence-based lesion detection with its broader endoscopic imaging environment. This represented an important evolution because AI became increasingly connected to the core endoscopy platform rather than treated solely as an external accessory.

Also in 2024, Olympus’ Odin Medical received FDA clearance for CADDIE, an AI technology designed to support detection of suspected colorectal polyps using a cloud-based architecture. Cloud deployment is strategically significant because it creates a pathway toward continuous software evolution, centralized management and broader intelligent-endoscopy applications.

During 2025 and into 2026, competitive activity increasingly shifted toward product updates, broader algorithm portfolios, cloud deployment, characterization capabilities and AI applications beyond simple colorectal lesion detection. Development pipelines across the industry increasingly include Barrett’s esophagus, ulcerative colitis, endoscopy quality assessment and other upper- and lower-GI applications.

Hospital and gastroenterology-group procurement strategies are also evolving. Early adoption was often physician champion driven. Larger deployments increasingly require approval from enterprise IT, cybersecurity, clinical quality and finance functions. This is raising the commercial bar for smaller AI vendors while favoring companies able to provide robust infrastructure and implementation support.

Another important development is the growing strategic connection between AI and endoscopy data. Video that historically disappeared after a procedure is increasingly viewed as a valuable clinical dataset. Capturing, structuring and analyzing this information can support quality improvement, research, physician education and future algorithm development.

The next major competitive stage is likely to involve multi-application AI platforms rather than individual algorithms. Once an endoscopy center has established secure connectivity and AI-compatible infrastructure, adding additional applications becomes economically easier. This creates potentially powerful installed-base advantages.

Conclusion

The U.S. AI-Enabled Gastroenterology Devices Market Size & Share is positioned to expand from approximately USD 1.28 billion in 2025 to USD 7.35 billion by 2035, representing a CAGR of 19.10% during 2026–2035.

The market’s growth is supported by one of the largest procedure bases suitable for clinical computer vision, expanding colorectal cancer screening demand, increasing regulatory maturity, strong outpatient gastroenterology economics and rapid improvements in machine-learning-enabled image analysis.

Colorectal polyp detection will remain the principal revenue engine in the near term, but the market will progressively diversify into lesion characterization, quality measurement, inflammatory bowel disease scoring, Barrett’s esophagus, capsule endoscopy, upper GI neoplasia, small-bowel disease and advanced endoscopic imaging.

The most important change through 2035 will be the transition from AI-assisted devices to intelligent gastroenterology ecosystems. Detection algorithms alone will become increasingly difficult to differentiate. Greater strategic value will move toward platforms capable of supporting multiple clinical applications while integrating with endoscopes, processors, cloud environments, quality programs and patient data.

Hospitals will prioritize clinical evidence, integration and enterprise economics. Ambulatory endoscopy centers will place greater emphasis on throughput, simplicity and per-procedure value. Large gastroenterology groups will increasingly use AI as both a clinical-quality tool and an operating platform for standardizing performance across sites.

Regionally, the South will remain the largest market, supported by Texas, Florida, North Carolina, Georgia, Tennessee and Virginia. The West is expected to record the fastest expansion, led by California and supported by Arizona, Washington, Colorado, Nevada and Utah. The Northeast will maintain outsized influence on clinical validation and premium technology adoption, while the Midwest will remain an important market for enterprise health-system deployment.

For manufacturers, investors and healthcare organizations, the central market question is no longer whether AI will enter gastroenterology. It already has. The more consequential questions are which AI functions will become sufficiently valuable to become routine elements of endoscopy, whether vendors can demonstrate sustainable workflow economics without dependence on standalone reimbursement, and which companies can convert individual algorithms into scalable clinical platforms.

Companies positioned to win will combine regulatory credibility, strong clinical evidence, low workflow burden, interoperability, cybersecurity, recurring software innovation and established access to U.S. gastroenterology purchasers. Those capabilities will determine which suppliers capture the transition from today’s computer-aided detection market to the substantially larger intelligent gastroenterology device ecosystem expected by 2035.

TABLE OF CONTENT

1. U.S. AI-Enabled Gastroenterology Devices Market: Market Introduction & Context

1.1. Market Definition
1.2. Scope of the Study
1.3. Research Methodology
1.3.1. Primary Data Collection
1.3.2. Secondary Data Sourcing
1.3.3. External Industry Collaborations
1.3.4. In-House Research Databases
1.3.5. AI Medical Device Market Sizing Framework
1.3.6. Analytical Frameworks & Forecasting Models
1.3.7. Data Triangulation, Validation and Final Report Publishing
1.4. Key Assumptions
1.5. Market Ecosystem Overview
1.6. Market Inclusion and Exclusion Criteria
1.7. Stakeholder Analysis
1.7.1. AI-Enabled Gastroenterology Device Manufacturers
1.7.2. Gastrointestinal Endoscopy System Manufacturers
1.7.3. Medical AI Software and Algorithm Developers
1.7.4. Component, Processor and Imaging Technology Suppliers
1.7.5. Hospitals and Integrated Delivery Networks
1.7.6. Gastroenterology Practices and Specialty GI Centers
1.7.7. Ambulatory Surgery Centers and Endoscopy Centers
1.7.8. Academic Medical Centers and Clinical Research Organizations
1.7.9. Group Purchasing Organizations and Healthcare Distributors
1.7.10. Payers, Regulators and Clinical Decision-Makers

What this section provides: This section defines the U.S. AI-enabled gastroenterology devices market boundary, study scope, inclusion criteria, research methodology, assumptions and stakeholder ecosystem, enabling clients to understand how device, software and AI-attributable revenues are measured and validated.

2. U.S. AI-Enabled Gastroenterology Devices Market: Executive Summary

2.1. Key Insights & Market Snapshot
2.2. Analyst Viewpoint
2.3. Market Attractiveness Index
2.4. Historical Market Summary, 2021–2024
2.5. Base Year Market Positioning, 2025
2.6. Forecast Outlook, 2026–2035
2.7. U.S. Market Size, 2021–2035 (US$ Billion)
2.8. Forecast CAGR Analysis, 2026–2035
2.9. High-Growth Opportunity Areas
2.10. AI Adoption Maturity Across U.S. Gastroenterology Workflows
2.11. Key Strategic Findings for Manufacturers, Providers and Investors

What this section provides: This section gives decision-makers a concise view of market size, growth trajectory, AI adoption maturity, leading applications, competitive intensity and high-priority commercial opportunities through 2035.

3. U.S. AI-Enabled Gastroenterology Devices Market: Market Dynamics & Outlook

3.1. Drivers and Their Impact Analysis
3.1.1. Rising U.S. Colorectal Cancer Screening and Surveillance Demand
3.1.2. Growing Adoption of AI-Assisted Colonoscopy
3.1.3. Need to Improve Adenoma and Polyp Detection Consistency
3.1.4. Increasing Gastrointestinal Endoscopy Procedure Volumes
3.1.5. Expansion of Ambulatory Gastroenterology and Endoscopy Centers
3.1.6. Rising Physician Workload and Demand for Decision-Support Technologies
3.1.7. Integration of AI with High-Definition and Advanced Endoscopic Imaging
3.1.8. Growing Demand for Objective Endoscopy Quality Measurement
3.1.9. Expansion of Enterprise Gastroenterology Networks and Practice Consolidation
3.2. Restraints and Their Impact Analysis
3.2.1. High Initial Hardware, Software and Integration Costs
3.2.2. Limited Standalone Reimbursement for AI-Assisted Endoscopy
3.2.3. Workflow Integration and Interoperability Challenges
3.2.4. Algorithm Performance Variability and False-Positive Alerts
3.2.5. Cybersecurity and Clinical Data Governance Concerns
3.2.6. Physician Resistance and Learning-Curve Considerations
3.3. Opportunities and Their Impact Analysis
3.3.1. Computer-Aided Detection Expansion Across Screening Colonoscopy
3.3.2. Computer-Aided Diagnosis and Optical Lesion Characterization
3.3.3. AI-Assisted Capsule Endoscopy Interpretation
3.3.4. AI Applications in Barrett’s Esophagus and Upper GI Neoplasia
3.3.5. AI-Based Inflammatory Bowel Disease Severity Assessment
3.3.6. Intelligent Endoscopy Quality and Workflow Analytics
3.3.7. Cloud-Based AI Deployment Across Multi-Site GI Networks
3.3.8. Integration of AI with Advanced Endoscopic Ultrasound
3.3.9. Enterprise AI Deployment Across Large Gastroenterology Groups
3.4. Challenges and Their Impact Analysis
3.4.1. Clinical Validation Across Diverse Patient Populations
3.4.2. Real-World Generalizability of AI Algorithms
3.4.3. Regulatory Requirements for Continuously Evolving AI Models
3.4.4. Integration with Legacy Endoscopy Equipment
3.4.5. Demonstrating Sustainable Return on Investment
3.5. Patent & Innovation Analysis, 2021–2025
3.6. AI Algorithm Development and Clinical Validation Landscape
3.7. Clinical Workflow Economics Analysis
3.8. Gastroenterology Procedure Economics Analysis
3.9. Hospital and ASC Capital Procurement Behavior Analysis
3.10. AI Adoption Barriers and Conversion Drivers

What this section provides: This section explains the clinical, technological, reimbursement, operational and economic forces shaping adoption of AI-enabled gastroenterology devices and helps clients assess both market upside and commercialization risk.

4. U.S. AI-Enabled Gastroenterology Devices Market: Market Environment & Industry Analysis

4.1. PESTEL Analysis
4.1.1. Political
4.1.2. Economic
4.1.3. Social
4.1.4. Technological
4.1.5. Environmental
4.1.6. Legal
4.2. Porter’s Five Forces Analysis
4.2.1. Threat of New Entrants
4.2.2. Bargaining Power of Buyers
4.2.3. Bargaining Power of Technology and Component Suppliers
4.2.4. Substitution Risk
4.2.5. Competitive Rivalry
4.3. AI-Enabled Gastroenterology Device Pricing Trend Analysis, 2025–2035
4.4. Value Chain & Technology Supply Chain Analysis
4.5. AI Algorithm Development-to-Commercialization Value Chain
4.6. Impact of Digitalization and Connected Endoscopy
4.7. Application & Innovation Landscape
4.8. FDA Regulatory Framework for AI/ML-Enabled Medical Devices
4.9. Software as a Medical Device Regulatory Considerations
4.10. Predetermined Change Control and Algorithm Update Considerations
4.11. CMS Reimbursement and Coverage Landscape
4.12. Colorectal Cancer Screening Reimbursement Environment
4.13. Healthcare Data Privacy and HIPAA Considerations
4.14. Cybersecurity Requirements for Connected Endoscopy Systems
4.15. Import/Export Restrictions & Tariff Impact
4.16. Government Initiatives and Colorectal Cancer Screening Programs
4.17. Impact of Escalating Geopolitical and Semiconductor Supply Risks
4.18. Hospital Value Analysis Committee Decision Framework
4.19. AI Technology Assessment Framework for Gastroenterology Providers
4.20. Clinical Evidence and Health-Economic Evidence Requirements

What this section provides: This section gives clients a comprehensive assessment of regulation, reimbursement, pricing, cybersecurity, technology development, supply-chain exposure, clinical evidence requirements and institutional purchasing dynamics affecting AI-enabled gastroenterology devices.

5. U.S. AI-Enabled Gastroenterology Devices Market – By Product Category

5.1. Overview
5.1.1. Segment Share Analysis, By Product Category, 2025 & 2035 (%)
5.1.2. Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
5.2. AI-Enabled Endoscopy and Colonoscopy Systems
5.2.1. Integrated AI Endoscopy Platforms
5.2.2. Add-On Computer-Aided Detection Modules
5.2.3. AI-Compatible Endoscopy Processors
5.2.4. Cloud-Connected Intelligent Endoscopy Systems
5.2.5. Advanced Visualization and AI Imaging Platforms
5.3. AI-Enabled Capsule Endoscopy Systems
5.3.1. Small-Bowel Capsule Endoscopy Systems
5.3.2. AI-Assisted Capsule Image Analysis Platforms
5.3.3. Bleeding and Lesion Detection Algorithms
5.3.4. Automated Frame Prioritization and Reading Support
5.4. AI-Assisted Endoscopic Ultrasound and Advanced GI Imaging Systems
5.4.1. AI-Enabled Endoscopic Ultrasound Systems
5.4.2. Pancreatic and Biliary Imaging AI
5.4.3. Lesion Characterization and Tissue Assessment Systems
5.4.4. Image-Guided Advanced Endoscopy Platforms
5.5. AI-Integrated GI Diagnostic and Monitoring Devices
5.5.1. AI-Assisted Motility Diagnostic Systems
5.5.2. Reflux and Functional GI Monitoring Platforms
5.5.3. Connected Gastrointestinal Diagnostic Devices
5.5.4. Algorithm-Assisted Physiologic Data Interpretation Systems
5.6. AI-Enabled Procedural Quality and Connected GI Device Platforms
5.6.1. Endoscopy Quality Measurement Systems
5.6.2. Automated Anatomical Landmark Recognition Platforms
5.6.3. Bowel Preparation Assessment Systems
5.6.4. AI-Assisted Procedure Documentation Platforms
5.6.5. Enterprise Endoscopy Analytics and Device Connectivity Platforms

What this section provides: This section identifies which AI-enabled gastroenterology device categories are expected to generate the highest revenue contribution and which product architectures are positioned for the strongest adoption through 2035.

6. U.S. AI-Enabled Gastroenterology Devices Market – By AI Functionality

6.1. Overview
6.1.1. Segment Share Analysis, By AI Functionality, 2025 & 2035 (%)
6.1.2. Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
6.2. Computer-Aided Detection
6.2.1. Colorectal Polyp Detection
6.2.2. Adenoma Detection
6.2.3. Upper GI Lesion Detection
6.2.4. Bleeding Detection
6.2.5. Small-Bowel Abnormality Detection
6.3. Computer-Aided Diagnosis and Lesion Characterization
6.3.1. Neoplastic vs. Non-Neoplastic Classification
6.3.2. Optical Histology Support
6.3.3. Colorectal Lesion Characterization
6.3.4. Barrett’s-Associated Dysplasia Assessment
6.3.5. Gastric and Esophageal Lesion Characterization
6.4. Procedural Quality and Completeness Assessment
6.4.1. Cecal Landmark Recognition
6.4.2. Withdrawal Quality Analysis
6.4.3. Mucosal Exposure Assessment
6.4.4. Bowel Preparation Quality Scoring
6.4.5. Procedure Completeness and Quality Analytics
6.5. Disease Severity and Quantitative Scoring
6.5.1. Ulcerative Colitis Severity Scoring
6.5.2. Crohn’s Disease Assessment
6.5.3. Mucosal Healing Evaluation
6.5.4. Barrett’s Esophagus Quantification
6.5.5. Longitudinal Disease Monitoring
6.6. Predictive Analytics and Clinical Decision Support
6.6.1. Risk Stratification
6.6.2. Surveillance Interval Decision Support
6.6.3. Disease Progression Prediction
6.6.4. Personalized Procedure and Treatment Support
6.6.5. Multi-Modal Clinical Decision Support

What this section provides: This section evaluates the AI functions creating clinical and commercial value across gastroenterology, from real-time lesion detection to diagnostic characterization, procedural quality measurement and predictive decision support.

7. U.S. AI-Enabled Gastroenterology Devices Market – By Clinical Application

7.1. Overview
7.1.1. Segment Share Analysis, By Clinical Application, 2025 & 2035 (%)
7.1.2. Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
7.2. Colorectal Cancer Screening and Polyp Detection
7.2.1. Screening Colonoscopy
7.2.2. Surveillance Colonoscopy
7.2.3. Adenoma Detection
7.2.4. Serrated Lesion Detection
7.2.5. Post-Polypectomy Surveillance Support
7.3. Barrett’s Esophagus and Upper GI Neoplasia
7.3.1. Barrett’s Esophagus Surveillance
7.3.2. Esophageal Dysplasia Detection
7.3.3. Esophageal Cancer Detection
7.3.4. Gastric Neoplasia Detection
7.3.5. Upper GI Lesion Characterization
7.4. Inflammatory Bowel Disease
7.4.1. Ulcerative Colitis
7.4.2. Crohn’s Disease
7.4.3. Endoscopic Disease Severity Scoring
7.4.4. Mucosal Healing Assessment
7.4.5. Treatment Response Monitoring
7.5. GI Bleeding and Small-Bowel Disease
7.5.1. Obscure Gastrointestinal Bleeding
7.5.2. Small-Bowel Ulcers
7.5.3. Vascular Lesions and Angioectasia
7.5.4. Small-Bowel Inflammation
7.5.5. Capsule Endoscopy Image Interpretation
7.6. Pancreaticobiliary and Advanced Endoscopic Imaging
7.6.1. Pancreatic Lesion Assessment
7.6.2. Biliary Disease
7.6.3. Endoscopic Ultrasound Interpretation
7.6.4. Subepithelial Lesion Assessment
7.6.5. Advanced Therapeutic Endoscopy Planning

What this section provides: This section helps clients identify the gastrointestinal disease areas and procedural applications with the greatest addressable AI opportunity, clinical need, procedure intensity and commercial growth potential.

8. U.S. AI-Enabled Gastroenterology Devices Market – By End User

8.1. Overview
8.1.1. Segment Share Analysis, By End User, 2025 & 2035 (%)
8.1.2. Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
8.2. Hospitals and Integrated Health Systems
8.2.1. Large Integrated Delivery Networks
8.2.2. Community Hospitals
8.2.3. Tertiary Referral Hospitals
8.2.4. Hospital-Owned Endoscopy Departments
8.3. Ambulatory Surgery Centers and Dedicated Endoscopy Centers
8.3.1. Independent Endoscopy Centers
8.3.2. Physician-Owned ASCs
8.3.3. Hospital-Affiliated ASCs
8.3.4. Multi-Site Endoscopy Networks
8.4. Gastroenterology Physician Practices
8.4.1. Independent Gastroenterology Practices
8.4.2. Large Consolidated GI Groups
8.4.3. Private Equity-Backed Gastroenterology Networks
8.4.4. Multispecialty Physician Organizations
8.5. Academic Medical Centers and Specialty GI Institutes
8.5.1. University Hospitals
8.5.2. Advanced Endoscopy Centers
8.5.3. IBD Specialty Centers
8.5.4. Gastrointestinal Oncology Centers
8.5.5. Clinical Trial and AI Validation Sites
8.6. Diagnostic and Multispecialty Care Networks
8.6.1. GI Diagnostic Centers
8.6.2. Multispecialty Outpatient Networks
8.6.3. Capsule Endoscopy Providers
8.6.4. Connected Diagnostic Care Networks

What this section provides: This section explains which U.S. healthcare settings are driving AI-enabled gastroenterology device purchasing, enterprise deployment, recurring software utilization and procedure-level adoption.

9. U.S. AI-Enabled Gastroenterology Devices Market: Procurement, Commercialization & Adoption Analysis

9.1. Overview
9.2. Direct Hospital and Health System Procurement
9.3. Integrated Delivery Network Enterprise Contracts
9.4. Gastroenterology Group Enterprise Procurement
9.5. Ambulatory Surgery Center Procurement
9.6. Group Purchasing Organization Influence
9.7. Capital Purchase Model
9.8. Subscription-Based AI Software Model
9.9. Per-Procedure and Usage-Based Commercial Models
9.10. Software Licensing and SaaS Commercial Models
9.11. Bundled Endoscopy Platform Procurement
9.12. Hardware-Plus-Software Commercial Models
9.13. Cloud-Based AI Deployment Economics
9.14. Enterprise Multi-Site Deployment Economics
9.15. Physician Champion-Led Adoption Model
9.16. Value Analysis Committee Procurement Model
9.17. Clinical Evidence Requirements for Procurement Approval
9.18. Cybersecurity and IT Approval Requirements
9.19. Interoperability and Legacy Equipment Compatibility
9.20. Return-on-Investment Analysis for AI-Assisted Endoscopy
9.21. Total Cost of Ownership Analysis
9.22. Vendor Selection Criteria
9.23. Contract Renewal and Software Upgrade Dynamics
9.24. Competitive Tendering and Vendor Consolidation Trends

What this section provides: This section explains how AI-enabled gastroenterology devices are evaluated, purchased, licensed and scaled across U.S. healthcare organizations, including capital, subscription, SaaS, enterprise and per-procedure commercial models.

10. U.S. AI-Enabled Gastroenterology Devices Market – By Geography
10.1. Introduction

10.1.1. Segment Share Analysis, By Geography, 2025 & 2035 (%)
10.1.2. Regional Market Size and Forecast, 2021–2035 (US$ Billion)
10.1.3. Regional Gastrointestinal Procedure Volume and Endoscopy Infrastructure Analysis
10.1.4. Regional AI Adoption Maturity Analysis
10.1.5. Regional Academic Medical Center and Gastroenterologist Density Analysis
10.1.6. Regional Colorectal Cancer Screening Environment
10.1.7. Regional Reimbursement and Procurement Dynamics
10.1.8. Regional AI-Enabled Endoscopy Opportunity Index

10.2. West Region

10.2.1. Regional Overview & Trends
10.2.2. West Region AI-Enabled Gastroenterology Device Manufacturers and Technology Ecosystem
10.2.3. West Region Market Size and Forecast, By State, 2021–2035 (US$ Billion)
10.2.4. West Region Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.5. West Region Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.6. West Region Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.7. West Region Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.8. West Region AI Adoption, Procurement and Commercial Opportunity Analysis

10.2.9. California

10.2.9.1. Overview
10.2.9.2. California Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.9.3. California Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.9.4. California Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.9.5. California Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.9.6. California AI Adoption and Procurement Opportunity Analysis

10.2.10. Washington

10.2.10.1. Overview
10.2.10.2. Washington Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.10.3. Washington Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.10.4. Washington Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.10.5. Washington Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.10.6. Washington AI Adoption and Procurement Opportunity Analysis

10.2.11. Arizona

10.2.11.1. Overview
10.2.11.2. Arizona Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.11.3. Arizona Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.11.4. Arizona Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.11.5. Arizona Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.11.6. Arizona AI Adoption and Procurement Opportunity Analysis

10.2.12. Colorado

10.2.12.1. Overview
10.2.12.2. Colorado Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.12.3. Colorado Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.12.4. Colorado Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.12.5. Colorado Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.12.6. Colorado AI Adoption and Procurement Opportunity Analysis

10.2.13. Oregon

10.2.13.1. Overview
10.2.13.2. Oregon Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.13.3. Oregon Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.13.4. Oregon Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.13.5. Oregon Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.13.6. Oregon AI Adoption and Procurement Opportunity Analysis

10.2.14. Utah

10.2.14.1. Overview
10.2.14.2. Utah Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.14.3. Utah Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.14.4. Utah Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.14.5. Utah Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.14.6. Utah AI Adoption and Procurement Opportunity Analysis

10.2.15. Nevada

10.2.15.1. Overview
10.2.15.2. Nevada Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.15.3. Nevada Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.15.4. Nevada Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.15.5. Nevada Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.15.6. Nevada AI Adoption and Procurement Opportunity Analysis

10.2.16. New Mexico

10.2.16.1. Overview
10.2.16.2. New Mexico Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.16.3. New Mexico Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.16.4. New Mexico Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.16.5. New Mexico Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.16.6. New Mexico AI Adoption and Procurement Opportunity Analysis

10.2.17. Idaho

10.2.17.1. Overview
10.2.17.2. Idaho Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.17.3. Idaho Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.17.4. Idaho Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.17.5. Idaho Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.17.6. Idaho AI Adoption and Procurement Opportunity Analysis

10.2.18. Montana

10.2.18.1. Overview
10.2.18.2. Montana Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.18.3. Montana Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.18.4. Montana Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.18.5. Montana Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.18.6. Montana AI Adoption and Procurement Opportunity Analysis

10.2.19. Wyoming

10.2.19.1. Overview
10.2.19.2. Wyoming Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.19.3. Wyoming Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.19.4. Wyoming Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.19.5. Wyoming Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.19.6. Wyoming AI Adoption and Procurement Opportunity Analysis

10.2.20. Alaska

10.2.20.1. Overview
10.2.20.2. Alaska Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.20.3. Alaska Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.20.4. Alaska Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.20.5. Alaska Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.20.6. Alaska AI Adoption and Procurement Opportunity Analysis

10.2.21. Hawaii

10.2.21.1. Overview
10.2.21.2. Hawaii Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.2.21.3. Hawaii Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.2.21.4. Hawaii Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.2.21.5. Hawaii Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.2.21.6. Hawaii AI Adoption and Procurement Opportunity Analysis

10.3. Northeast Region

10.3.1. Regional Overview & Trends
10.3.2. Northeast Region AI-Enabled Gastroenterology Device Manufacturers and Technology Ecosystem
10.3.3. Northeast Region Market Size and Forecast, By State, 2021–2035 (US$ Billion)
10.3.4. Northeast Region Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.5. Northeast Region Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.6. Northeast Region Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.7. Northeast Region Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.8. Northeast Region AI Adoption, Procurement and Commercial Opportunity Analysis

10.3.9. New York

10.3.9.1. Overview
10.3.9.2. New York Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.9.3. New York Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.9.4. New York Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.9.5. New York Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.9.6. New York AI Adoption and Procurement Opportunity Analysis

10.3.10. Massachusetts

10.3.10.1. Overview
10.3.10.2. Massachusetts Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.10.3. Massachusetts Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.10.4. Massachusetts Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.10.5. Massachusetts Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.10.6. Massachusetts AI Adoption and Procurement Opportunity Analysis

10.3.11. New Jersey

10.3.11.1. Overview
10.3.11.2. New Jersey Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.11.3. New Jersey Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.11.4. New Jersey Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.11.5. New Jersey Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.11.6. New Jersey AI Adoption and Procurement Opportunity Analysis

10.3.12. Pennsylvania

10.3.12.1. Overview
10.3.12.2. Pennsylvania Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.12.3. Pennsylvania Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.12.4. Pennsylvania Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.12.5. Pennsylvania Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.12.6. Pennsylvania AI Adoption and Procurement Opportunity Analysis

10.3.13. Connecticut

10.3.13.1. Overview
10.3.13.2. Connecticut Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.13.3. Connecticut Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.13.4. Connecticut Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.13.5. Connecticut Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.13.6. Connecticut AI Adoption and Procurement Opportunity Analysis

10.3.14. Maine

10.3.14.1. Overview
10.3.14.2. Maine Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.14.3. Maine Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.14.4. Maine Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.14.5. Maine Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.14.6. Maine AI Adoption and Procurement Opportunity Analysis

10.3.15. Vermont

10.3.15.1. Overview
10.3.15.2. Vermont Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.15.3. Vermont Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.15.4. Vermont Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.15.5. Vermont Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.15.6. Vermont AI Adoption and Procurement Opportunity Analysis

10.3.16. New Hampshire

10.3.16.1. Overview
10.3.16.2. New Hampshire Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.16.3. New Hampshire Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.16.4. New Hampshire Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.16.5. New Hampshire Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.16.6. New Hampshire AI Adoption and Procurement Opportunity Analysis

10.3.17. Rhode Island

10.3.17.1. Overview
10.3.17.2. Rhode Island Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.17.3. Rhode Island Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.17.4. Rhode Island Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.17.5. Rhode Island Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.17.6. Rhode Island AI Adoption and Procurement Opportunity Analysis

10.3.18. Delaware

10.3.18.1. Overview
10.3.18.2. Delaware Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.3.18.3. Delaware Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.3.18.4. Delaware Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.3.18.5. Delaware Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.3.18.6. Delaware AI Adoption and Procurement Opportunity Analysis

10.4. South Region

10.4.1. Regional Overview & Trends
10.4.2. South Region AI-Enabled Gastroenterology Device Manufacturers and Technology Ecosystem
10.4.3. South Region Market Size and Forecast, By State, 2021–2035 (US$ Billion)
10.4.4. South Region Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.5. South Region Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.6. South Region Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.7. South Region Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.8. South Region AI Adoption, Procurement and Commercial Opportunity Analysis

10.4.9. Texas

10.4.9.1. Overview
10.4.9.2. Texas Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.9.3. Texas Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.9.4. Texas Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.9.5. Texas Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.9.6. Texas AI Adoption and Procurement Opportunity Analysis

10.4.10. Florida

10.4.10.1. Overview
10.4.10.2. Florida Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.10.3. Florida Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.10.4. Florida Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.10.5. Florida Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.10.6. Florida AI Adoption and Procurement Opportunity Analysis

10.4.11. Georgia

10.4.11.1. Overview
10.4.11.2. Georgia Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.11.3. Georgia Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.11.4. Georgia Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.11.5. Georgia Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.11.6. Georgia AI Adoption and Procurement Opportunity Analysis

10.4.12. North Carolina

10.4.12.1. Overview
10.4.12.2. North Carolina Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.12.3. North Carolina Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.12.4. North Carolina Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.12.5. North Carolina Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.12.6. North Carolina AI Adoption and Procurement Opportunity Analysis

10.4.13. Tennessee

10.4.13.1. Overview
10.4.13.2. Tennessee Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.13.3. Tennessee Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.13.4. Tennessee Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.13.5. Tennessee Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.13.6. Tennessee AI Adoption and Procurement Opportunity Analysis

10.4.14. South Carolina

10.4.14.1. Overview
10.4.14.2. South Carolina Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.14.3. South Carolina Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.14.4. South Carolina Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.14.5. South Carolina Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.14.6. South Carolina AI Adoption and Procurement Opportunity Analysis

10.4.15. Alabama

10.4.15.1. Overview
10.4.15.2. Alabama Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.15.3. Alabama Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.15.4. Alabama Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.15.5. Alabama Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.15.6. Alabama AI Adoption and Procurement Opportunity Analysis

10.4.16. Mississippi

10.4.16.1. Overview
10.4.16.2. Mississippi Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.16.3. Mississippi Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.16.4. Mississippi Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.16.5. Mississippi Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.16.6. Mississippi AI Adoption and Procurement Opportunity Analysis

10.4.17. Louisiana

10.4.17.1. Overview
10.4.17.2. Louisiana Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.17.3. Louisiana Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.17.4. Louisiana Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.17.5. Louisiana Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.17.6. Louisiana AI Adoption and Procurement Opportunity Analysis

10.4.18. Arkansas

10.4.18.1. Overview
10.4.18.2. Arkansas Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.18.3. Arkansas Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.18.4. Arkansas Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.18.5. Arkansas Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.18.6. Arkansas AI Adoption and Procurement Opportunity Analysis

10.4.19. Kentucky

10.4.19.1. Overview
10.4.19.2. Kentucky Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.19.3. Kentucky Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.19.4. Kentucky Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.19.5. Kentucky Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.19.6. Kentucky AI Adoption and Procurement Opportunity Analysis

10.4.20. Oklahoma

10.4.20.1. Overview
10.4.20.2. Oklahoma Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.20.3. Oklahoma Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.20.4. Oklahoma Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.20.5. Oklahoma Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.20.6. Oklahoma AI Adoption and Procurement Opportunity Analysis

10.4.21. Virginia

10.4.21.1. Overview
10.4.21.2. Virginia Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.21.3. Virginia Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.21.4. Virginia Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.21.5. Virginia Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.21.6. Virginia AI Adoption and Procurement Opportunity Analysis

10.4.22. Maryland

10.4.22.1. Overview
10.4.22.2. Maryland Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.22.3. Maryland Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.22.4. Maryland Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.22.5. Maryland Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.22.6. Maryland AI Adoption and Procurement Opportunity Analysis

10.4.23. West Virginia

10.4.23.1. Overview
10.4.23.2. West Virginia Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.4.23.3. West Virginia Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.4.23.4. West Virginia Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.4.23.5. West Virginia Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.4.23.6. West Virginia AI Adoption and Procurement Opportunity Analysis

10.5. Midwest Region

10.5.1. Regional Overview & Trends
10.5.2. Midwest Region AI-Enabled Gastroenterology Device Manufacturers and Technology Ecosystem
10.5.3. Midwest Region Market Size and Forecast, By State, 2021–2035 (US$ Billion)
10.5.4. Midwest Region Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.5. Midwest Region Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.6. Midwest Region Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.7. Midwest Region Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.8. Midwest Region AI Adoption, Procurement and Commercial Opportunity Analysis

10.5.9. Illinois

10.5.9.1. Overview
10.5.9.2. Illinois Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.9.3. Illinois Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.9.4. Illinois Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.9.5. Illinois Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.9.6. Illinois AI Adoption and Procurement Opportunity Analysis

10.5.10. Ohio

10.5.10.1. Overview
10.5.10.2. Ohio Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.10.3. Ohio Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.10.4. Ohio Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.10.5. Ohio Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.10.6. Ohio AI Adoption and Procurement Opportunity Analysis

10.5.11. Michigan

10.5.11.1. Overview
10.5.11.2. Michigan Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.11.3. Michigan Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.11.4. Michigan Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.11.5. Michigan Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.11.6. Michigan AI Adoption and Procurement Opportunity Analysis

10.5.12. Minnesota

10.5.12.1. Overview
10.5.12.2. Minnesota Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.12.3. Minnesota Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.12.4. Minnesota Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.12.5. Minnesota Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.12.6. Minnesota AI Adoption and Procurement Opportunity Analysis

10.5.13. Indiana

10.5.13.1. Overview
10.5.13.2. Indiana Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.13.3. Indiana Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.13.4. Indiana Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.13.5. Indiana Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.13.6. Indiana AI Adoption and Procurement Opportunity Analysis

10.5.14. Wisconsin

10.5.14.1. Overview
10.5.14.2. Wisconsin Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.14.3. Wisconsin Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.14.4. Wisconsin Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.14.5. Wisconsin Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.14.6. Wisconsin AI Adoption and Procurement Opportunity Analysis

10.5.15. Missouri

10.5.15.1. Overview
10.5.15.2. Missouri Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.15.3. Missouri Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.15.4. Missouri Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.15.5. Missouri Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.15.6. Missouri AI Adoption and Procurement Opportunity Analysis

10.5.16. Iowa

10.5.16.1. Overview
10.5.16.2. Iowa Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.16.3. Iowa Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.16.4. Iowa Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.16.5. Iowa Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.16.6. Iowa AI Adoption and Procurement Opportunity Analysis

10.5.17. Kansas

10.5.17.1. Overview
10.5.17.2. Kansas Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.17.3. Kansas Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.17.4. Kansas Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.17.5. Kansas Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.17.6. Kansas AI Adoption and Procurement Opportunity Analysis

10.5.18. Nebraska

10.5.18.1. Overview
10.5.18.2. Nebraska Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.18.3. Nebraska Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.18.4. Nebraska Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.18.5. Nebraska Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.18.6. Nebraska AI Adoption and Procurement Opportunity Analysis

10.5.19. North Dakota

10.5.19.1. Overview
10.5.19.2. North Dakota Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.19.3. North Dakota Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.19.4. North Dakota Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.19.5. North Dakota Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.19.6. North Dakota AI Adoption and Procurement Opportunity Analysis

10.5.20. South Dakota

10.5.20.1. Overview
10.5.20.2. South Dakota Market Size and Forecast, By Product Category, 2021–2035 (US$ Billion)
10.5.20.3. South Dakota Market Size and Forecast, By AI Functionality, 2021–2035 (US$ Billion)
10.5.20.4. South Dakota Market Size and Forecast, By Clinical Application, 2021–2035 (US$ Billion)
10.5.20.5. South Dakota Market Size and Forecast, By End User, 2021–2035 (US$ Billion)
10.5.20.6. South Dakota AI Adoption and Procurement Opportunity Analysis

What this section provides: This section delivers detailed regional and state-level analysis across all 50 U.S. states, enabling clients to identify AI-endoscopy adoption hotspots, high-volume GI procedure markets, academic innovation hubs, ASC opportunities and state-level commercial priorities.

11. U.S. AI-Enabled Gastroenterology Devices Market: Competitive Landscape & Company Profiles

11.1. Market Share Analysis, 2025
11.2. Competitive Intensity Analysis
11.3. Company Positioning Matrix
11.3.1. Leaders
11.3.2. Challengers
11.3.3. Innovators
11.3.4. Emerging Players
11.4. Competitive Benchmarking, By AI Capability
11.5. Competitive Benchmarking, By Endoscopy Platform Compatibility
11.6. Competitive Benchmarking, By FDA Clearance Status
11.7. Competitive Benchmarking, By Cloud and Enterprise Deployment Capability
11.8. Strategic Partnerships, Licensing and Distribution Analysis
11.9. Mergers, Acquisitions and Investment Activity
11.10. Company Profiles

11.10.1. Medtronic
11.10.2. Cosmo Pharmaceuticals N.V. / Cosmo Intelligent Medical Devices
11.10.3. Olympus Corporation
11.10.4. Odin Medical Ltd. / Odin Vision
11.10.5. FUJIFILM Healthcare Americas Corporation
11.10.6. Iterative Health
11.10.7. PENTAX Medical
11.10.8. Wision A.I.
11.10.9. Magentiq Eye
11.10.10. NEC Corporation
11.10.11. AnX Robotica
11.10.12. CapsoVision
11.10.13. Virgo Surgical Video Solutions
11.10.14. Satisfai Health
11.10.15. EndoSound
11.10.16. CDx Diagnostics
11.10.17. PathAI
11.10.18. Ibex Medical Analytics
11.10.19. Proscia
11.10.20. Paige
11.10.21. GE HealthCare
11.10.22. Siemens Healthineers
11.10.23. Philips
11.10.24. Ambu A/S
11.10.25. SonoScape Medical

Note: Each company profile will include company overview, AI-enabled gastroenterology portfolio, U.S. market strategy, endoscopy platform positioning, FDA/regulatory status, clinical evidence, AI capability, commercialization model, partnerships, financial or funding positioning where available, and recent developments.

What this section provides: This section gives clients competitor benchmarking, market positioning, regulatory visibility, AI portfolio comparison, partnership intelligence and strategic assessment of established medtech companies and specialist gastroenterology AI innovators.

12. U.S. AI-Enabled Gastroenterology Devices Market: Future Market Outlook, 2026–2035

12.1. Scenario Analysis
12.1.1. Optimistic Scenario
12.1.2. Realistic Scenario
12.1.3. Pessimistic Scenario
12.2. Disruptive Technologies Impact
12.2.1. Next-Generation Computer-Aided Detection
12.2.2. Computer-Aided Diagnosis and Optical Histology
12.2.3. Generative AI-Assisted Endoscopy Documentation
12.2.4. Cloud-Based Intelligent Endoscopy
12.2.5. AI-Assisted Capsule Endoscopy
12.2.6. AI-Based IBD Scoring and Monitoring
12.2.7. AI-Assisted Barrett’s Esophagus Surveillance
12.2.8. AI-Enabled Endoscopic Ultrasound
12.2.9. Multi-Modal Gastroenterology AI Platforms
12.2.10. Autonomous and Semi-Autonomous Endoscopy Support
12.3. Future FDA Regulatory Evolution
12.4. Future Reimbursement Scenarios for AI-Assisted Procedures
12.5. Emerging Business Models
12.6. Shift from Standalone Algorithms to Integrated AI Platforms
12.7. Enterprise Gastroenterology AI Adoption Outlook
12.8. Business Opportunities for Startups and Existing Players
12.9. Investment Prioritization Matrix
12.10. Technology Adoption Curve, 2026–2035
12.11. Future Competitive Structure and Consolidation Outlook

What this section provides: This section prepares clients for future AI technology shifts, regulatory and reimbursement evolution, emerging commercial models, platform consolidation and investment opportunities through 2035.

13. U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations

13.1. Recommendations for AI-Enabled Gastroenterology Device Manufacturers
13.2. Recommendations for Traditional Endoscopy Manufacturers
13.3. Recommendations for AI Software and Algorithm Developers
13.4. Recommendations for Hospitals and Integrated Health Systems
13.5. Recommendations for Gastroenterology Practices and GI Networks
13.6. Recommendations for Ambulatory Surgery Centers and Endoscopy Centers
13.7. Recommendations for Investors and Private Equity Firms
13.8. Recommendations for Distributors and Channel Partners
13.9. Recommendations for New Entrants and Startups
13.10. U.S. Go-to-Market Strategy Considerations
13.11. FDA and Clinical Evidence Strategy
13.12. Pricing and Commercial Model Strategy
13.13. Enterprise Contracting Strategy
13.14. Hospital and ASC Value Proposition Development
13.15. Product Positioning and Portfolio Expansion Guidance
13.16. Partnership, Licensing and Acquisition Strategy
13.17. State-Level Market Entry Prioritization
13.18. Competitive Differentiation Framework

What this section provides: This section converts market intelligence into actionable recommendations for product development, U.S. commercialization, regulatory planning, clinical evidence generation, enterprise sales, pricing, geographic expansion and competitive differentiation.

14. U.S. AI-Enabled Gastroenterology Devices Market: Disclaimer

14.1. Scope Limitation
14.2. Market Definition Limitation
14.3. AI-Attributable Revenue Estimation Limitation
14.4. Data Use Limitation
14.5. Historical Data Limitation
14.6. Forecasting Limitation
14.7. Regulatory and Reimbursement Limitation
14.8. Company Information Limitation
14.9. Legal Disclaimer
14.10. Third-Party Data Disclaimer

What this section provides: This section clarifies the report’s market boundaries, AI-revenue estimation methodology limitations, forecasting assumptions, regulatory considerations, third-party data limitations and legal terms.

List of Tables

TABLE 1: List of Data Sources
TABLE 2: U.S. AI-Enabled Gastroenterology Devices Market: Market Definition and Scope
TABLE 3: U.S. AI-Enabled Gastroenterology Devices Market: Research Methodology Framework
TABLE 4: U.S. AI-Enabled Gastroenterology Devices Market: Market Inclusion and Exclusion Criteria
TABLE 5: U.S. AI-Enabled Gastroenterology Devices Market: Key Assumptions
TABLE 6: U.S. AI-Enabled Gastroenterology Devices Market: Market Ecosystem and Stakeholder Analysis
TABLE 7: U.S. AI-Enabled Gastroenterology Devices Market: Executive Summary Snapshot, 2025
TABLE 8: U.S. AI-Enabled Gastroenterology Devices Market: Historical Market Size, 2021–2024 (US$ Billion)
TABLE 9: U.S. AI-Enabled Gastroenterology Devices Market: Base Year Market Positioning, 2025
TABLE 10: U.S. AI-Enabled Gastroenterology Devices Market: Forecast Market Size, 2026–2035 (US$ Billion)
TABLE 11: U.S. AI-Enabled Gastroenterology Devices Market: Year-wise Market Size, 2021–2035 (US$ Billion)
TABLE 12: U.S. AI-Enabled Gastroenterology Devices Market: Forecast CAGR Analysis, 2026–2035
TABLE 13: U.S. AI-Enabled Gastroenterology Devices Market: Market Attractiveness Index
TABLE 14: U.S. AI-Enabled Gastroenterology Devices Market: High-Growth Opportunity Areas
TABLE 15: U.S. AI-Enabled Gastroenterology Devices Market: Drivers; Impact Analysis
TABLE 16: U.S. AI-Enabled Gastroenterology Devices Market: Restraints; Impact Analysis
TABLE 17: U.S. AI-Enabled Gastroenterology Devices Market: Opportunities; Impact Analysis
TABLE 18: U.S. AI-Enabled Gastroenterology Devices Market: Challenges; Impact Analysis
TABLE 19: U.S. AI-Enabled Gastroenterology Devices Market: Patent & Innovation Analysis, 2021–2025
TABLE 20: U.S. AI-Enabled Gastroenterology Devices Market: AI Algorithm Development and Clinical Validation Landscape
TABLE 21: U.S. AI-Enabled Gastroenterology Devices Market: Clinical Workflow Economics Matrix
TABLE 22: U.S. AI-Enabled Gastroenterology Devices Market: Gastroenterology Procedure Economics Analysis
TABLE 23: U.S. AI-Enabled Gastroenterology Devices Market: Hospital and ASC Capital Procurement Behavior Matrix
TABLE 24: U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption Barriers and Conversion Drivers
TABLE 25: U.S. AI-Enabled Gastroenterology Devices Market: Clinical Validation and Real-World Generalizability Matrix
TABLE 26: U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption ROI Drivers
TABLE 27: U.S. AI-Enabled Gastroenterology Devices Market: PESTEL Analysis
TABLE 28: U.S. AI-Enabled Gastroenterology Devices Market: Porter’s Five Forces Analysis
TABLE 29: U.S. AI-Enabled Gastroenterology Devices Market: Pricing Trend Analysis, 2025–2035
TABLE 30: U.S. AI-Enabled Gastroenterology Devices Market: Value Chain Analysis
TABLE 31: U.S. AI-Enabled Gastroenterology Devices Market: Technology Supply Chain Analysis
TABLE 32: U.S. AI-Enabled Gastroenterology Devices Market: AI Development-to-Commercialization Value Chain
TABLE 33: U.S. AI-Enabled Gastroenterology Devices Market: Digitalization and Connected Endoscopy Impact
TABLE 34: U.S. AI-Enabled Gastroenterology Devices Market: Application & Innovation Landscape
TABLE 35: U.S. AI-Enabled Gastroenterology Devices Market: FDA Regulatory Framework Analysis
TABLE 36: U.S. AI-Enabled Gastroenterology Devices Market: Software as a Medical Device Regulatory Framework
TABLE 37: U.S. AI-Enabled Gastroenterology Devices Market: Predetermined Change Control and Algorithm Update Considerations
TABLE 38: U.S. AI-Enabled Gastroenterology Devices Market: CMS Reimbursement and Coverage Landscape
TABLE 39: U.S. AI-Enabled Gastroenterology Devices Market: Colorectal Cancer Screening Reimbursement Environment
TABLE 40: U.S. AI-Enabled Gastroenterology Devices Market: HIPAA and Clinical Data Privacy Considerations
TABLE 41: U.S. AI-Enabled Gastroenterology Devices Market: Cybersecurity Requirements for Connected GI Devices
TABLE 42: U.S. AI-Enabled Gastroenterology Devices Market: Hospital Value Analysis Committee Decision Framework
TABLE 43: U.S. AI-Enabled Gastroenterology Devices Market: Product Category Snapshot, 2025
TABLE 44: Segment Dashboard; Definition and Scope, by Product Category
TABLE 45: U.S. AI-Enabled Gastroenterology Devices Market, by Product Category, 2021–2035 (US$ Billion)
TABLE 46: U.S. AI-Enabled Gastroenterology Devices Market: Segment Share Analysis, by Product Category, 2025 & 2035 (%)
TABLE 47: AI-Enabled Endoscopy and Colonoscopy Systems Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 48: AI-Enabled Capsule Endoscopy Systems Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 49: AI-Assisted Endoscopic Ultrasound and Advanced GI Imaging Systems Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 50: AI-Integrated GI Diagnostic and Monitoring Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 51: AI-Enabled Procedural Quality and Connected GI Device Platforms Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 52: U.S. AI-Enabled Gastroenterology Devices Market: AI Functionality Snapshot, 2025
TABLE 53: Segment Dashboard; Definition and Scope, by AI Functionality
TABLE 54: U.S. AI-Enabled Gastroenterology Devices Market, by AI Functionality, 2021–2035 (US$ Billion)
TABLE 55: U.S. AI-Enabled Gastroenterology Devices Market: Segment Share Analysis, by AI Functionality, 2025 & 2035 (%)
TABLE 56: Computer-Aided Detection Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 57: Computer-Aided Diagnosis and Lesion Characterization Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 58: Procedural Quality and Completeness Assessment Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 59: Disease Severity and Quantitative Scoring Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 60: Predictive Analytics and Clinical Decision Support Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 61: U.S. AI-Enabled Gastroenterology Devices Market: Clinical Application Snapshot, 2025
TABLE 62: Segment Dashboard; Definition and Scope, by Clinical Application
TABLE 63: U.S. AI-Enabled Gastroenterology Devices Market, by Clinical Application, 2021–2035 (US$ Billion)
TABLE 64: U.S. AI-Enabled Gastroenterology Devices Market: Segment Share Analysis, by Clinical Application, 2025 & 2035 (%)
TABLE 65: Colorectal Cancer Screening and Polyp Detection Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 66: Barrett’s Esophagus and Upper GI Neoplasia Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 67: Inflammatory Bowel Disease Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 68: GI Bleeding and Small-Bowel Disease Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 69: Pancreaticobiliary and Advanced Endoscopic Imaging Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 70: U.S. AI-Enabled Gastroenterology Devices Market: End User Snapshot, 2025
TABLE 71: Segment Dashboard; Definition and Scope, by End User
TABLE 72: U.S. AI-Enabled Gastroenterology Devices Market, by End User, 2021–2035 (US$ Billion)
TABLE 73: U.S. AI-Enabled Gastroenterology Devices Market: Segment Share Analysis, by End User, 2025 & 2035 (%)
TABLE 74: Hospitals and Integrated Health Systems Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 75: Ambulatory Surgery Centers and Dedicated Endoscopy Centers Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 76: Gastroenterology Physician Practices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 77: Academic Medical Centers and Specialty GI Institutes Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 78: Diagnostic and Multispecialty Care Networks Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 79: U.S. AI-Enabled Gastroenterology Devices Market: Procurement and Commercialization Snapshot, 2025
TABLE 80: Direct Hospital and Health System Procurement Analysis
TABLE 81: Integrated Delivery Network Enterprise Contracting Analysis
TABLE 82: Gastroenterology Group Enterprise Procurement Analysis
TABLE 83: Ambulatory Surgery Center Procurement Analysis
TABLE 84: U.S. AI-Enabled Gastroenterology Devices Market: Commercial Model Comparison
TABLE 85: U.S. AI-Enabled Gastroenterology Devices Market: Cloud-Based AI Deployment Economics
TABLE 86: U.S. AI-Enabled Gastroenterology Devices Market: Enterprise Multi-Site Deployment Economics
TABLE 87: U.S. AI-Enabled Gastroenterology Devices Market: Clinical Evidence Requirements for Procurement Approval
TABLE 88: U.S. AI-Enabled Gastroenterology Devices Market: Cybersecurity and IT Approval Requirements
TABLE 89: U.S. AI-Enabled Gastroenterology Devices Market: Interoperability and Legacy Equipment Compatibility
TABLE 90: U.S. AI-Enabled Gastroenterology Devices Market: Return-on-Investment Analysis
TABLE 91: U.S. AI-Enabled Gastroenterology Devices Market: Total Cost of Ownership Analysis
TABLE 92: U.S. AI-Enabled Gastroenterology Devices Market: Vendor Selection Criteria
TABLE 93: U.S. AI-Enabled Gastroenterology Devices Market: Regional Snapshot, 2025
TABLE 94: Segment Dashboard; Definition and Scope, by Geography
TABLE 95: U.S. AI-Enabled Gastroenterology Devices Market, by Region, 2021–2035 (US$ Billion)
TABLE 96: U.S. AI-Enabled Gastroenterology Devices Market: Regional Share Analysis, 2025 & 2035 (%)
TABLE 97: U.S. AI-Enabled Gastroenterology Devices Market: Regional GI Procedure Volume and Endoscopy Infrastructure Analysis
TABLE 98: U.S. AI-Enabled Gastroenterology Devices Market: Regional AI Adoption Maturity Analysis
TABLE 99: U.S. AI-Enabled Gastroenterology Devices Market: Regional Colorectal Cancer Screening Environment
TABLE 100: U.S. AI-Enabled Gastroenterology Devices Market: Regional AI Opportunity Index
TABLE 101: West Region U.S. AI-Enabled Gastroenterology Devices Market: Regional Overview and Trends
TABLE 102: West Region U.S. AI-Enabled Gastroenterology Devices Market, by State, 2021–2035 (US$ Billion)
TABLE 103: West Region U.S. AI-Enabled Gastroenterology Devices Market, by Product Category, 2021–2035 (US$ Billion)
TABLE 104: West Region U.S. AI-Enabled Gastroenterology Devices Market, by AI Functionality, 2021–2035 (US$ Billion)
TABLE 105: West Region U.S. AI-Enabled Gastroenterology Devices Market, by Clinical Application, 2021–2035 (US$ Billion)
TABLE 106: West Region U.S. AI-Enabled Gastroenterology Devices Market, by End User, 2021–2035 (US$ Billion)
TABLE 107: West Region U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption and Procurement Opportunity
TABLE 108: California AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 109: Washington AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 110: Arizona AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 111: Colorado AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 112: Oregon AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 113: Utah AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 114: Nevada AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 115: New Mexico AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 116: Idaho AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 117: Montana AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 118: Wyoming AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 119: Alaska AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 120: Hawaii AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 121: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market: Regional Overview and Trends
TABLE 122: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market, by State, 2021–2035 (US$ Billion)
TABLE 123: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market, by Product Category, 2021–2035 (US$ Billion)
TABLE 124: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market, by AI Functionality, 2021–2035 (US$ Billion)
TABLE 125: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market, by Clinical Application, 2021–2035 (US$ Billion)
TABLE 126: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market, by End User, 2021–2035 (US$ Billion)
TABLE 127: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption and Procurement Opportunity
TABLE 128: New York AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 129: Massachusetts AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 130: New Jersey AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 131: Pennsylvania AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 132: Connecticut AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 133: Maine AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 134: Vermont AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 135: New Hampshire AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 136: Rhode Island AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 137: Delaware AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 138: South Region U.S. AI-Enabled Gastroenterology Devices Market: Regional Overview and Trends
TABLE 139: South Region U.S. AI-Enabled Gastroenterology Devices Market, by State, 2021–2035 (US$ Billion)
TABLE 140: South Region U.S. AI-Enabled Gastroenterology Devices Market, by Product Category, 2021–2035 (US$ Billion)
TABLE 141: South Region U.S. AI-Enabled Gastroenterology Devices Market, by AI Functionality, 2021–2035 (US$ Billion)
TABLE 142: South Region U.S. AI-Enabled Gastroenterology Devices Market, by Clinical Application, 2021–2035 (US$ Billion)
TABLE 143: South Region U.S. AI-Enabled Gastroenterology Devices Market, by End User, 2021–2035 (US$ Billion)
TABLE 144: South Region U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption and Procurement Opportunity
TABLE 145: Texas AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 146: Florida AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 147: Georgia AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 148: North Carolina AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 149: Tennessee AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 150: South Carolina AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 151: Alabama AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 152: Mississippi AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 153: Louisiana AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 154: Arkansas AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 155: Kentucky AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 156: Oklahoma AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 157: Virginia AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 158: Maryland AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 159: West Virginia AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 160: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market: Regional Overview and Trends
TABLE 161: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market, by State, 2021–2035 (US$ Billion)
TABLE 162: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market, by Product Category, 2021–2035 (US$ Billion)
TABLE 163: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market, by AI Functionality, 2021–2035 (US$ Billion)
TABLE 164: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market, by Clinical Application, 2021–2035 (US$ Billion)
TABLE 165: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market, by End User, 2021–2035 (US$ Billion)
TABLE 166: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market: AI Adoption and Procurement Opportunity
TABLE 167: Illinois AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 168: Ohio AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 169: Michigan AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 170: Minnesota AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 171: Indiana AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 172: Wisconsin AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 173: Missouri AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 174: Iowa AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 175: Kansas AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 176: Nebraska AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 177: North Dakota AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 178: South Dakota AI-Enabled Gastroenterology Devices Market Size and Forecast, 2021–2035 (US$ Billion)
TABLE 179: U.S. AI-Enabled Gastroenterology Devices Market: Competitive Landscape Snapshot, 2025
TABLE 180: U.S. AI-Enabled Gastroenterology Devices Market: Key Company Market Share Analysis, 2025
TABLE 181: U.S. AI-Enabled Gastroenterology Devices Market: Company Positioning Matrix
TABLE 182: U.S. AI-Enabled Gastroenterology Devices Market: Competitive Benchmarking, by AI Capability
TABLE 183: U.S. AI-Enabled Gastroenterology Devices Market: Endoscopy Platform Compatibility Benchmarking
TABLE 184: U.S. AI-Enabled Gastroenterology Devices Market: FDA Clearance Status Benchmarking
TABLE 185: U.S. AI-Enabled Gastroenterology Devices Market: Cloud and Enterprise Deployment Benchmarking
TABLE 186: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Partnerships, Licensing, M&A and Investment Activity
TABLE 187: Medtronic: Company Profile
TABLE 188: Cosmo Pharmaceuticals N.V. / Cosmo Intelligent Medical Devices: Company Profile
TABLE 189: Olympus Corporation: Company Profile
TABLE 190: Odin Medical Ltd. / Odin Vision: Company Profile
TABLE 191: FUJIFILM Healthcare Americas Corporation: Company Profile
TABLE 192: Iterative Health: Company Profile
TABLE 193: PENTAX Medical: Company Profile
TABLE 194: Wision A.I.: Company Profile
TABLE 195: Magentiq Eye: Company Profile
TABLE 196: NEC Corporation: Company Profile
TABLE 197: AnX Robotica: Company Profile
TABLE 198: CapsoVision: Company Profile
TABLE 199: Virgo Surgical Video Solutions: Company Profile
TABLE 200: Satisfai Health: Company Profile
TABLE 201: EndoSound: Company Profile
TABLE 202: CDx Diagnostics: Company Profile
TABLE 203: PathAI: Company Profile
TABLE 204: Ibex Medical Analytics: Company Profile
TABLE 205: Proscia: Company Profile
TABLE 206: Paige: Company Profile
TABLE 207: GE HealthCare: Company Profile
TABLE 208: Siemens Healthineers: Company Profile
TABLE 209: Philips: Company Profile
TABLE 210: Ambu A/S: Company Profile
TABLE 211: SonoScape Medical: Company Profile
TABLE 212: U.S. AI-Enabled Gastroenterology Devices Market: Future Market Scenario Analysis, 2026–2035
TABLE 213: U.S. AI-Enabled Gastroenterology Devices Market: Disruptive Technologies Impact Matrix
TABLE 214: U.S. AI-Enabled Gastroenterology Devices Market: Next-Generation Computer-Aided Detection Opportunity
TABLE 215: U.S. AI-Enabled Gastroenterology Devices Market: CADx and Optical Histology Opportunity
TABLE 216: U.S. AI-Enabled Gastroenterology Devices Market: Generative AI-Assisted Endoscopy Documentation Outlook
TABLE 217: U.S. AI-Enabled Gastroenterology Devices Market: Cloud-Based Intelligent Endoscopy Outlook
TABLE 218: U.S. AI-Enabled Gastroenterology Devices Market: AI-Assisted Capsule Endoscopy Opportunity
TABLE 219: U.S. AI-Enabled Gastroenterology Devices Market: AI-Based IBD Scoring and Monitoring Opportunity
TABLE 220: U.S. AI-Enabled Gastroenterology Devices Market: AI-Assisted Barrett’s Esophagus Surveillance Opportunity
TABLE 221: U.S. AI-Enabled Gastroenterology Devices Market: AI-Enabled Endoscopic Ultrasound Opportunity
TABLE 222: U.S. AI-Enabled Gastroenterology Devices Market: Multi-Modal AI Platform Opportunity
TABLE 223: U.S. AI-Enabled Gastroenterology Devices Market: Autonomous and Semi-Autonomous Endoscopy Support Outlook
TABLE 224: U.S. AI-Enabled Gastroenterology Devices Market: Future FDA Regulatory Evolution
TABLE 225: U.S. AI-Enabled Gastroenterology Devices Market: Future Reimbursement Scenario Analysis
TABLE 226: U.S. AI-Enabled Gastroenterology Devices Market: Emerging Business Models
TABLE 227: U.S. AI-Enabled Gastroenterology Devices Market: Technology Adoption Curve, 2026–2035
TABLE 228: U.S. AI-Enabled Gastroenterology Devices Market: Future Competitive Structure and Consolidation Outlook
TABLE 229: U.S. AI-Enabled Gastroenterology Devices Market: Investment Prioritization Matrix
TABLE 230: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for AI-Enabled Device Manufacturers
TABLE 231: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for Traditional Endoscopy Manufacturers
TABLE 232: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for AI Software Developers
TABLE 233: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for Hospitals and Health Systems
TABLE 234: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for Gastroenterology Practices and GI Networks
TABLE 235: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for ASCs and Endoscopy Centers
TABLE 236: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for Investors and Private Equity Firms
TABLE 237: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for Distributors and Channel Partners
TABLE 238: U.S. AI-Enabled Gastroenterology Devices Market: Strategic Recommendations for New Entrants and Startups
TABLE 239: U.S. AI-Enabled Gastroenterology Devices Market: Go-to-Market Strategy Considerations
TABLE 240: U.S. AI-Enabled Gastroenterology Devices Market: FDA and Clinical Evidence Strategy
TABLE 241: U.S. AI-Enabled Gastroenterology Devices Market: Pricing and Commercial Model Strategy
TABLE 242: U.S. AI-Enabled Gastroenterology Devices Market: Enterprise Contracting Strategy
TABLE 243: U.S. AI-Enabled Gastroenterology Devices Market: State-Level Market Entry Prioritization
TABLE 244: U.S. AI-Enabled Gastroenterology Devices Market: Competitive Differentiation Framework
TABLE 245: U.S. AI-Enabled Gastroenterology Devices Market: Scope Limitation
TABLE 246: U.S. AI-Enabled Gastroenterology Devices Market: Market Definition Limitation
TABLE 247: U.S. AI-Enabled Gastroenterology Devices Market: AI-Attributable Revenue Estimation Limitation
TABLE 248: U.S. AI-Enabled Gastroenterology Devices Market: Data Use Limitation
TABLE 249: U.S. AI-Enabled Gastroenterology Devices Market: Historical Data Limitation
TABLE 250: U.S. AI-Enabled Gastroenterology Devices Market: Forecasting Limitation
TABLE 251: U.S. AI-Enabled Gastroenterology Devices Market: Regulatory and Reimbursement Limitation
TABLE 252: U.S. AI-Enabled Gastroenterology Devices Market: Company Information Limitation
TABLE 253: U.S. AI-Enabled Gastroenterology Devices Market: Legal Disclaimer
TABLE 254: U.S. AI-Enabled Gastroenterology Devices Market: Third-Party Data Disclaimer

List of Figures

FIGURE 1: U.S. AI-Enabled Gastroenterology Devices Market Segmentation
FIGURE 2: Market Research Methodology
FIGURE 3: U.S. AI-Enabled Gastroenterology Devices Market Ecosystem
FIGURE 4: Executive Market Snapshot, 2025
FIGURE 5: U.S. AI-Enabled Gastroenterology Devices Market Size, Historical Trend Analysis, 2021–2024 (US$ Billion)
FIGURE 6: U.S. AI-Enabled Gastroenterology Devices Market Size, Forecast and Trend Analysis, 2026–2035 (US$ Billion)
FIGURE 7: U.S. AI-Enabled Gastroenterology Devices Market Year-wise Growth Curve, 2021–2035
FIGURE 8: Market Attractiveness Analysis
FIGURE 9: U.S. AI-Enabled Gastroenterology Devices Market Dynamics
FIGURE 10: AI Innovation & Patent Landscape, 2021–2025
FIGURE 11: Clinical Workflow Economics Framework
FIGURE 12: Hospital and ASC Capital Procurement Decision Framework
FIGURE 13: PESTEL Analysis
FIGURE 14: Porter’s Five Forces Analysis
FIGURE 15: Value Chain and Technology Supply Chain Analysis
FIGURE 16: AI Development-to-Commercialization Framework
FIGURE 17: FDA Regulatory Framework for AI/ML-Enabled Gastroenterology Devices
FIGURE 18: CMS Reimbursement and Coverage Landscape
FIGURE 19: Cybersecurity and Connected Endoscopy Framework
FIGURE 20: Product Category Segment Market Share Analysis, 2025 & 2035
FIGURE 21: Product Category Segment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 22: AI-Enabled Endoscopy and Colonoscopy Systems Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 23: AI-Enabled Capsule Endoscopy Systems Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 24: AI-Assisted EUS and Advanced GI Imaging Systems Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 25: AI-Integrated GI Diagnostic and Monitoring Devices Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 26: AI-Enabled Procedural Quality and Connected GI Platforms Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 27: AI Functionality Segment Market Share Analysis, 2025 & 2035
FIGURE 28: AI Functionality Segment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 29: Computer-Aided Detection Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 30: Computer-Aided Diagnosis and Lesion Characterization Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 31: Procedural Quality and Completeness Assessment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 32: Disease Severity and Quantitative Scoring Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 33: Predictive Analytics and Clinical Decision Support Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 34: Clinical Application Segment Market Share Analysis, 2025 & 2035
FIGURE 35: Clinical Application Segment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 36: Colorectal Cancer Screening and Polyp Detection Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 37: Barrett’s Esophagus and Upper GI Neoplasia Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 38: Inflammatory Bowel Disease Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 39: GI Bleeding and Small-Bowel Disease Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 40: Pancreaticobiliary and Advanced Endoscopic Imaging Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 41: End User Segment Market Share Analysis, 2025 & 2035
FIGURE 42: End User Segment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 43: Hospitals and Integrated Health Systems Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 44: Ambulatory Surgery Centers and Dedicated Endoscopy Centers Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 45: Gastroenterology Physician Practices Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 46: Academic Medical Centers and Specialty GI Institutes Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 47: Diagnostic and Multispecialty Care Networks Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 48: AI-Enabled Gastroenterology Device Procurement Ecosystem
FIGURE 49: Capital Purchase vs. Subscription vs. SaaS Commercial Model Comparison
FIGURE 50: Enterprise Multi-Site AI Deployment Framework
FIGURE 51: Clinical Evidence and Procurement Approval Framework
FIGURE 52: AI-Enabled Endoscopy Interoperability Framework
FIGURE 53: AI-Assisted Endoscopy Return-on-Investment Framework
FIGURE 54: Total Cost of Ownership Framework
FIGURE 55: Vendor Selection and Contracting Decision Matrix
FIGURE 56: Regional Segment Market Share Analysis, 2025 & 2035
FIGURE 57: Regional Segment Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 58: West Region U.S. AI-Enabled Gastroenterology Devices Market Share and Adoption Landscape, 2025
FIGURE 59: West Region Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 60: California AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 61: Washington AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 62: Arizona AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 63: Colorado AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 64: Oregon AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 65: Utah AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 66: Nevada AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 67: New Mexico AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 68: Idaho AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 69: Montana AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 70: Wyoming AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 71: Alaska AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 72: Hawaii AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 73: Northeast Region U.S. AI-Enabled Gastroenterology Devices Market Share and Adoption Landscape, 2025
FIGURE 74: Northeast Region Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 75: New York AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 76: Massachusetts AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 77: New Jersey AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 78: Pennsylvania AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 79: Connecticut AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 80: Maine AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 81: Vermont AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 82: New Hampshire AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 83: Rhode Island AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 84: Delaware AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 85: South Region U.S. AI-Enabled Gastroenterology Devices Market Share and Adoption Landscape, 2025
FIGURE 86: South Region Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 87: Texas AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 88: Florida AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 89: Georgia AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 90: North Carolina AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 91: Tennessee AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 92: South Carolina AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 93: Alabama AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 94: Mississippi AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 95: Louisiana AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 96: Arkansas AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 97: Kentucky AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 98: Oklahoma AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 99: Virginia AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 100: Maryland AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 101: West Virginia AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 102: Midwest Region U.S. AI-Enabled Gastroenterology Devices Market Share and Adoption Landscape, 2025
FIGURE 103: Midwest Region Market Size Forecast and Trend Analysis, 2021–2035 (US$ Billion)
FIGURE 104: Illinois AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 105: Ohio AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 106: Michigan AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 107: Minnesota AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 108: Indiana AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 109: Wisconsin AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 110: Missouri AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 111: Iowa AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 112: Kansas AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 113: Nebraska AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 114: North Dakota AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 115: South Dakota AI-Enabled Gastroenterology Devices Market Size and Trend Analysis, 2021–2035
FIGURE 116: Competitive Landscape; Key Company Market Share Analysis, 2025
FIGURE 117: Company Positioning Matrix
FIGURE 118: AI Capability Benchmarking of Key Players
FIGURE 119: Endoscopy Platform Compatibility Benchmarking
FIGURE 120: FDA Clearance and Regulatory Positioning of Key Players
FIGURE 121: Cloud and Enterprise Deployment Capability Benchmarking
FIGURE 122: Strategic Partnerships, Licensing, M&A and Investment Activity
FIGURE 123: U.S. AI-Enabled Gastroenterology Devices Innovation Roadmap
FIGURE 124: Future Market Scenario Analysis, 2026–2035
FIGURE 125: Disruptive Technologies Impact Matrix
FIGURE 126: Computer-Aided Detection and CADx Evolution Roadmap
FIGURE 127: Cloud-Based Intelligent Endoscopy Growth Roadmap
FIGURE 128: AI-Assisted Capsule Endoscopy Opportunity Map
FIGURE 129: Multi-Modal Gastroenterology AI Platform Roadmap
FIGURE 130: AI Technology Adoption Curve, 2026–2035
FIGURE 131: Investment Prioritization Matrix
FIGURE 132: Strategic Growth Roadmap for U.S. AI-Enabled Gastroenterology Device Companies
FIGURE 133: U.S. Go-to-Market Strategy Framework
FIGURE 134: Product Positioning and Portfolio Expansion Framework
FIGURE 135: State-Level Commercial Opportunity Prioritization Framework
FIGURE 136: Report Scope and Disclaimer Framework