ROCKVILLE, MARYLAND , August 27, 2026 — The Artificial Intelligence in Ultrasound Imaging Market is valued at USD 3.9 billion in 2026 and is forecast to reach USD 16.8 billion by 2036, recording a compound annual growth rate of 15.7%. The market surpassed USD 3.4 billion in 2025. Absolute opportunity is projected at USD 12.9 billion by 2036, led by Image Analysis Software, Image Acquisition, General Imaging, Hospitals and Deep Learning.
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Key Findings
• Market size moves from USD 3.9 billion (2026) to USD 16.8 billion (2036) at 15.7% CAGR.
• Image Analysis Software holds an estimated 38.0% share in 2026.
• Image Acquisition is projected to hold 36.0% share in 2026.
• General Imaging is anticipated to capture 40.0% share in 2026.
• Hospitals are estimated to represent 43.0% share in 2026.
• Deep Learning is forecast to account for 39.0% share in 2026.
• Country CAGRs range from 17.1% (USA) to 13.8% (Singapore).
Growth Drivers
• AI-assisted acquisition reducing operator-dependent variability, which reduces repeat scans and supports guided capture (North America, Europe, Asia Pacific; medium term, 2-4 years).
• Hospital throughput and diagnostic capacity pressure, improving examination capacity (USA, UK, Germany, Canada; near to medium term, ≤4 years).
• Expansion of portable and point-of-care ultrasound, extending imaging into bedside care (USA, Japan, South Korea, Singapore; medium term, 2-4 years).
• Automated measurement and structured reporting requirements that standardize measurements and reporting (global hospital and imaging networks; medium term, 2-4 years).
• Lifecycle rules for machine-learning medical devices that support governed software updates (USA, Canada, UK, South Korea, Singapore; short term, ≤2 years).
Acquisition guidance helps non-specialist users capture usable images with fewer repeat attempts. Workflow standardization raises demand for software that fits enterprise governance and places image capture and report steps inside existing clinical systems. Portable use expansion supports focused scans in emergency and critical-care settings.
Segment Analysis by Product, Technology and Application
By AI Imaging Solution
• Image Analysis Software leads at 38.0% share in 2026 because automated measurements reduce manual review time.
• Decision Support Software adds value during lesion and severity assessment.
• Workflow Automation focuses on documentation and reporting.
By Clinical Workflow
• Image Acquisition leads with 36.0% share in 2026 as real-time enhancement improves scan usability.
• Diagnostic Interpretation supports lesion review.
• Point-of-Care Ultrasound extends scanning into emergency and critical-care environments.
By Application Area
• General Imaging holds 40.0% share in 2026 owing to abdominal and liver imaging use.
• Cardiovascular Imaging remains important for cardiac assessments.
• Obstetrics and Gynecology uses AI for fetal views and biometric checks.
By End User
• Hospitals account for 43.0% share in 2026 due to clinical governance, user credentialing and fleet-wide quality control.
• Diagnostic Imaging Centers emphasize exam speed and reporting consistency.
• Community Healthcare Centers contribute where point-of-care ultrasound supports focused bedside decisions.
By AI Technology
• Deep Learning holds 39.0% share in 2026 through anatomy recognition and image segmentation.
• Computer Vision is used during view detection and scan guidance.
• Natural Language Processing supports structured reporting.
Country-Level Growth Comparison
Country CAGR (2026-2036) One-line commercial condition
USA 17.1% FDA-cleared AI functions and large hospital buyer base for regulated medical-device software
Japan 16.5% Diagnostic imaging capability and demand for reproducible examinations
Germany 15.9% Hospital-system scale and regulated demand for high-risk medical AI
UK 15.4% Diagnostic capacity pressure and community imaging expansion
Canada 14.8% Regulatory clarity for machine-learning medical devices (Health Canada April 2026 MLMD guidance) and distributed diagnostic access
South Korea 14.3% Domestic ultrasound manufacturing and women’s health AI activity
Singapore 13.8% Healthcare AI governance and software-as-a-medical-device controls (MOH and HSA)
The displayed country range spans 3.3 percentage points and forms three practical adoption bands through 2036. Full report coverage includes North America, Europe, Asia Pacific, Central and South America, and the Middle East and Africa.
Competitive Landscape
Key companies 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.
• EchoNous, Inc.
GE HealthCare shows the direct position through cardiac acquisition guidance and handheld ultrasound integration. Siemens Healthineers and Philips add enterprise ultrasound depth. Samsung Medison strengthens women’s health AI through the Sonio acquisition.
Recent Developments
• GE HealthCare Technologies Inc. (April 3, 2024): Introduces Caption AI on Vscan Air SL wireless handheld ultrasound system to help clinicians capture diagnostic-quality cardiac images.
• Samsung Medison Co., Ltd. (September 2024): Completes Sonio acquisition, strengthening fetal ultrasound AI depth.
• Health Sciences Authority (Singapore) (December 4, 2024): Pilot run of Change Management Program (CMP) for SaMD, including machine learning-enabled SaMD.
• Clarius Mobile Health Corp. (April 25, 2025): FDA clears new Clarius Prostate AI to help physicians assess and diagnose common urologic conditions.
• Butterfly Network, Inc. (November 17, 2025): Launches Compass AI to power the next generation of POCUS program management.
• Butterfly Network, Inc. (March 30, 2026): Secures first FDA clearance for blind sweep ultrasound AI tool for women’s health.
• Health Canada (April 2026): Issues MLMD guidance clarifying product lifecycle evidence.
Restraints
• Clinical validation across devices and users raises validation cost (global; medium term, 2-4 years).
• Cybersecurity and software change-control obligations extend compliance review (North America, Europe, and advanced Asian markets; short to medium term, ≤4 years).
• Integration with hospital records and imaging infrastructure lengthens deployment (large hospital systems; medium term, 2-4 years).
• Budget cycles and uncertain reimbursement delay lower-priority procurement (global; long term, ≥4 years).
Evidence and generalizability require clear performance limits across devices and user groups. Governance and integration extend purchase timelines because connected ultrasound software handles patient images and measurements. Training burden requires simple escalation rules for bedside users.
How to Choose
Procurement and R&D teams evaluating AI ultrasound solutions should apply the following criteria drawn from the report’s analysis of validation evidence, integration fit and governance:
1. Confirm clinical validation evidence across multiple devices and user groups, including documented performance limits.
2. Assess integration depth with existing clinical systems, picture archiving and communication systems, and medical records.
3. Review cybersecurity posture and software change-control processes aligned with lifecycle rules for machine-learning medical devices.
4. Evaluate real-time acquisition guidance quality and automated measurement repeatability for the intended clinical workflow (acquisition, interpretation or point-of-care).
5. Verify post-market update governance and credentialing support for hospital fleet-level deployment.
6. Compare training and escalation protocols so bedside or non-specialist users have clear scan-escalation rules.
Report Scope
The report covers AI-enabled ultrasound software for guided acquisition, image enhancement, analysis, reporting and workflow governance. Segmentation includes AI Imaging Solution (Image Analysis Software, Decision Support Software, Workflow Automation, Predictive Imaging Analytics), Clinical Workflow (Image Acquisition, Diagnostic Interpretation, Screening and Monitoring, Point-of-Care Ultrasound), Application Area (General Imaging, Cardiovascular Imaging, Obstetrics and Gynecology, Musculoskeletal Imaging), End User (Hospitals, Diagnostic Imaging Centers and others), and AI Technology (Deep Learning, Computer Vision, Natural Language Processing, Predictive Analytics). Regions covered are North America, Europe, Asia Pacific, Central and South America, and the Middle East and Africa. Key countries profiled are the USA, Japan, Germany, UK, Canada, South Korea and Singapore. The analysis draws on 120+ sources, 35+ company portfolios, 25+ countries and more than 20 industry interviews. Forecast period is 2026 to 2036.
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