Rockville, Maryland, United States – September 9, 2026 – The U.S. Food and Drug Administration's updated AI-enabled medical device list includes multiple ultrasound systems and AI-supported radiology technologies cleared during 2026, underscoring the growing role of artificial intelligence in regulated diagnostic imaging. In February 2026, the FDA also granted De Novo authorization to Delivery Date AI, an ultrasound-based software system designed for delivery-date prediction.

According to Fact.MR, the global artificial intelligence in ultrasound imaging market is valued at USD 3.9 billion in 2026 and is projected to reach USD 16.8 billion by 2036, expanding at a 15.7% CAGR. The market surpassed USD 3.4 billion in 2025, creating an estimated absolute opportunity of USD 12.9 billion through 2036.

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Why AI Is Becoming Part of the Ultrasound Workflow

Ultrasound has traditionally depended heavily on operator skill. The quality of an examination can vary according to probe positioning, image acquisition, anatomy recognition, and the user's experience.

Artificial intelligence is changing that equation.

AI tools can guide image acquisition, identify anatomical structures, automate measurements, enhance images, and support interpretation. Instead of functioning only after an ultrasound examination is completed, newer systems increasingly provide assistance during the scan itself.

This shift has implications for equipment procurement. Hospitals are no longer evaluating ultrasound systems solely on image quality and hardware specifications. Software capability, clinical validation, cybersecurity, integration, and update governance are becoming part of the purchasing decision.

The FDA says AI technologies in medical devices can support image acquisition and processing, early disease detection, diagnosis, prognosis, and risk assessment.

Image Analysis Software Leads AI Imaging Solutions

Image Analysis Software is projected to account for 38.0% of the AI imaging solution segment in 2026, making it the leading category.

Automated image analysis can reduce manual measurement requirements and support more consistent interpretation.

The technology can identify structures, segment anatomy, quantify measurements, and highlight findings for review. These functions are particularly relevant in high-volume imaging departments where repeated manual measurements can consume specialist time.

Decision-support software and workflow automation add further functionality. Predictive imaging analytics can also contribute to risk assessment where validated algorithms are available.

The commercial opportunity depends on clinical performance. An algorithm that works effectively in one ultrasound platform or patient population may not deliver identical results across different devices and users.

Image Acquisition Holds the Largest Workflow Share

Image Acquisition is expected to represent 36.0% of the clinical workflow segment in 2026.

The emphasis on acquisition reflects a fundamental characteristic of ultrasound: interpretation depends on obtaining usable images first.

AI-guided acquisition can provide prompts, quality feedback, view recognition, and other forms of assistance during scanning. This may help less-experienced users capture images that meet predefined quality requirements.

The opportunity extends into portable and point-of-care ultrasound.

Emergency departments, intensive-care units, community settings, and bedside applications can benefit from software that helps users follow defined scanning protocols.

For manufacturers, this creates an opportunity to position AI as part of the imaging workflow rather than as an independent software add-on.

General Imaging Leads Application Demand

General Imaging is projected to capture 40.0% of the market by application area in 2026.

Abdominal and liver examinations provide broad use cases for automated anatomy recognition and measurement.

AI can assist with repeatable measurements and image-quality assessment across examinations. Consistency is particularly valuable when patients undergo repeated imaging over time.

Cardiovascular imaging remains another important application, particularly where automated measurements can support cardiac assessments.

Obstetrics and gynecology is also becoming an important application area, with AI being used for fetal views, biometric measurements, and examination guidance.

Hospitals Remain the Largest End User

Hospitals are forecast to account for 43.0% of the end-user segment in 2026.

Hospitals operate large imaging fleets and have formal processes for credentialing users, validating technologies, managing cybersecurity, and overseeing clinical quality.

This gives hospital procurement teams a central role in AI ultrasound adoption.

Rather than evaluating a software function in isolation, hospitals increasingly need to understand how an AI-enabled ultrasound system fits within their existing imaging infrastructure.

Integration with picture archiving and communication systems, electronic medical records, reporting workflows, and enterprise cybersecurity policies can determine whether a pilot becomes a wider deployment.

Deep Learning Holds the Technology Lead

Deep Learning is projected to account for 39.0% of the AI technology segment in 2026.

Deep-learning models can support anatomy recognition, segmentation, image analysis, and automated measurements.

Computer vision complements these capabilities through view detection and scan guidance. Natural language processing can assist structured reporting, while predictive analytics supports risk-oriented applications.

The FDA's regulatory framework increasingly emphasizes lifecycle considerations for AI-enabled medical devices. The agency's 2025 draft guidance addresses lifecycle management and marketing submissions for AI-enabled device software functions, while its 2026 digital-health guidance portfolio continues to evolve.

This places greater emphasis on software change control and ongoing performance management.

What's Driving Market Expansion?

Operator-dependent variability is a central driver.

AI-guided acquisition can help standardize image capture and reduce repeat examinations. For hospitals facing diagnostic capacity pressure, improved workflow efficiency can have commercial value.

The expansion of portable ultrasound is another growth factor. Handheld systems are moving ultrasound closer to patients, creating demand for technology that supports clinicians who may not specialize in sonography.

Automated measurements and structured reporting also create opportunities. Once AI functions are integrated into the imaging workflow, hospitals can use them to support quality assurance and reporting consistency.

“AI is changing ultrasound buying from a hardware-only choice into a workflow and evidence choice,” said Shambhu Nath Jha, Senior Consultant at Fact.MR. “Hospital teams are expected to compare guidance quality and measurement repeatability. Integration depth and cybersecurity are expected to face the same review before wider use. Companies with reliable imaging and governed software updates are better placed to turn pilots into network use.”

Validation and Integration Remain Key Barriers

AI ultrasound adoption faces practical limitations.

Clinical validation across different ultrasound devices and user groups can require significant investment. Algorithm performance can change when imaging conditions, patient demographics, or equipment characteristics differ from the development environment.

Cybersecurity is another concern. Connected ultrasound systems handle patient images and clinical measurements, making access controls, data protection, and software-update procedures important procurement considerations.

Integration can also lengthen deployment timelines. Hospitals need AI systems to work within existing imaging archives, medical-record environments, and reporting systems.

Budget cycles and uncertain reimbursement can further delay purchases, particularly when an AI function is considered an enhancement rather than a core clinical requirement.

United States Leads Country Growth

The United States is projected to expand at a 17.1% CAGR from 2026 to 2036, the fastest growth among the countries profiled by Fact.MR.

The country's large hospital buyer base and established FDA pathway for AI-enabled medical devices support adoption.

Japan follows at 16.5% CAGR, supported by diagnostic imaging capability and demand for reproducible examinations. Germany is projected to grow at 15.9%, while the United Kingdom reaches 15.4%.

Canada is forecast at 14.8% CAGR, South Korea at 14.3%, and Singapore at 13.8% through 2036.

The markets differ in regulatory systems, hospital structures, reimbursement and imaging infrastructure. Vendors therefore need country-specific evidence and deployment strategies rather than relying on a single global commercialization model.

Competitive Landscape

Key companies identified by Fact.MR include GE HealthCare Technologies Inc., Siemens Healthineers AG, Koninklijke Philips N.V., Canon Medical Systems Corporation, Samsung Medison Co., Ltd., Butterfly Network, Inc., Clarius Mobile Health Corp., and EchoNous, Inc.

Competition spans established ultrasound manufacturers and specialist point-of-care imaging companies.

GE HealthCare, Siemens Healthineers, Philips, Canon Medical Systems, and Samsung Medison bring established ultrasound platforms and hospital relationships. Specialist companies such as Butterfly Network, Clarius, and EchoNous focus more heavily on portable or point-of-care ultrasound applications.

The competitive threshold is increasingly moving toward evidence and workflow integration. Vendors need to demonstrate that AI functions improve acquisition, measurement or interpretation without creating additional uncertainty for clinicians.

The FDA's current AI-enabled device list illustrates the breadth of regulated AI applications and is updated periodically as additional devices receive authorization.

Artificial Intelligence in Ultrasound Imaging Market Snapshot

2025 market value: USD 3.4 billion+
2026 market value: USD 3.9 billion
2036 projected value: USD 16.8 billion
CAGR, 2026–2036: 15.7%
Absolute opportunity: USD 12.9 billion
Leading AI imaging solution: Image Analysis Software, 38.0%
Leading clinical workflow: Image Acquisition, 36.0%
Leading application area: General Imaging, 40.0%
Leading end user: Hospitals, 43.0%
Leading AI technology: Deep Learning, 39.0%
Fastest-growing profiled country: United States, 17.1% CAGR
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Report Scope and Methodology

The Fact.MR study evaluates the artificial intelligence in ultrasound imaging market across AI imaging solution, clinical workflow, application area, end user, AI technology, and region.

AI imaging solutions include Image Analysis Software, Decision Support Software, Workflow Automation, and Predictive Imaging Analytics.

Clinical workflows cover Image Acquisition, Diagnostic Interpretation, Screening and Monitoring, and Point-of-Care Ultrasound. Application areas include General Imaging, Cardiovascular Imaging, Obstetrics and Gynecology, and Musculoskeletal Imaging.

End users include Hospitals, Diagnostic Imaging Centers, Specialty Clinics, Research Institutes, Ambulatory Surgical Centers, Community Healthcare Centers, and Primary Care Networks.

AI technologies covered include Deep Learning, Computer Vision, Natural Language Processing, and Predictive Analytics.

The geographic scope includes North America, Europe, Asia Pacific, Central and South America, and the Middle East and Africa, with detailed country analysis for the United States, Japan, Germany, the United Kingdom, Canada, South Korea, and Singapore.

Fact.MR states that the study draws on 120+ sources, 35+ company portfolios, 25+ countries, and more than 20 industry interviews, combining primary research, desk research, market sizing, forecasting, company assessment, and data validation.

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About Fact.MR

Fact.MR is an initiative of Eminent Research and Advisory Services, providing market intelligence and syndicated research across healthcare, food and beverage, consumer goods, technology, industrial goods, and other sectors. The company operates from offices in Rockville, Maryland, United States, and Dublin, Ireland.

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Disclosure

This release is based on Fact.MR syndicated research. Market figures represent estimates and forecasts available as of the publication date and may be revised as additional information becomes available.