The Artificial Intelligence (AI) in the Radiology Report Generation market is forecast to grow at a CAGR of 35.1%, reaching USD 6.3 billion in 2031 from USD 1.4 billion in 2026.
AI’s transformative role in healthcare has completely changed the radiology report generation market. Through this transformative technology that automatically produces reports, radiologists’ workloads are reduced while productivity increases. Consequently, AI algorithms analyze and interpret X-ray images using radiology machines with exceptional speed and prior accuracy. This means that the AI-generated reports are highly precise, making it possible to detect anomalies at an earlier stage and provide better treatment for patients. In addition, AI-powered technologies quicken radiologists’ workflows, thus enabling them to concentrate on more challenging cases. Thus, with increasing demand for fast and accurate diagnoses, AI has proved to be a game-changer in the radiology report generation market.
The increasing volume of medical imaging data is anticipated to increase the demand
The growing volume of medical imaging data is a major driving force in the AI in radiology report generation market. Digital imaging technologies have been adopted by medical facilities and healthcare organizations, resulting in a tremendous increase in the number of medical images produced. This avalanche of data comprises X-rays, MRIs, CT scans, and other diagnostic tools that constitute a big repository of important information. Such a huge amount of images can be hard to analyze manually, consuming more time and being open to human mistakes.
Deep learning algorithms, in particular, excel in processing and interpreting such data at unparalleled speed and precision. AI algorithms can swiftly analyze and extract significant information from these pictures, assisting radiologists in producing thorough and exact reports. The capacity of AI to successfully handle this data flood has accelerated its acceptance in radiology, greatly improving healthcare results.
Rising demand for automated report generation is anticipated to drive market growth
The need for greater efficiency, accuracy, and workflow optimization is driving the growing demand for automated report generation in AI in the radiology report-generating market. Traditional manual report-generating procedures can be time-consuming and prone to human mistakes, potentially resulting in patient care delays. Automation with AI-powered algorithms streamlines the report-generating process, drastically cutting turnaround times and enhancing radiology departments' overall efficiency.
AI systems can evaluate medical pictures and extract pertinent information to provide complete and standardized reports using modern natural language processing (NLP) and image recognition algorithms. This saves radiologists time and assures uniform and accurate reporting, supporting improved patient care and allowing prompt communication among healthcare professionals. The need for automated report production continues to rise as healthcare institutions strive for better diagnosis and patient outcomes.
Service offerings & data analytics insights
Offering AI-powered radiology solutions as subscription-based services is a trend that businesses can take advantage of. This model can be profitable because it creates a steady stream of income. This further enables suppliers to maintain and enhance their AI algorithms while offering healthcare providers affordable solutions. This model is attractive to subscribers or healthcare providers because users can access regular updates and new features whenever the service provider makes them available.
In addition to diagnostic tools, businesses can use the data produced by AI systems to give healthcare organizations insightful analyses and insights. Predictive analytics for population health management, treatment efficacy evaluation, and patient outcomes are all included in this, opening up new revenue streams.
Regulatory compliance & high initial costs are anticipated to impede market growth
Implementing AI in radiology may be hampered by strict regulatory requirements and compliance issues, which can be burdensome for market participants in certain situations. AI systems must follow regulations, particularly regarding patient data privacy and security. It can be expensive and time-consuming to ensure the right precautions are taken. Radiology AI algorithms need big datasets for validation and training. There may be less access to high-quality, diverse data for particular medical conditions in certain nations or areas. This can hinder the development and uptake of AI solutions, especially in specialized fields of radiology.
Further, implementing AI systems, including buying hardware and software that uses AI, can require large upfront costs. Smaller or more financially strapped healthcare facilities and institutions may find it difficult to justify these costs, which is a significant barrier to adoption and the market's potential for revenue growth.
North America is witnessing exponential growth during the forecast period
North America is regarded as the market leader in AI in radiology report generation. This is due to the region's robust infrastructure, superior healthcare systems, and substantial expenditures in AI technology. The existence of world-class medical research institutes, technological firms, and cooperation between healthcare providers and AI developers has accelerated its implementation in radiology practices. Furthermore, favorable regulatory frameworks and an emphasis on integrating AI into healthcare processes have aided North America's leadership in improving AI-powered radiology report production systems. Hence, the regional AI in the radiology report generation market has expanded significantly.
October 2025: Aidoc announced that its aiOS platform, powered by the CARE foundation model, received Breakthrough Device Designation from the U.S. FDA. The solution enables AI-assisted triage of multiple acute conditions from CT scans within a unified workflow, accelerating diagnostic insights and improving radiology efficiency.
September 2025: GE HealthCare unveiled a new AI-supported solution at the ASTRO 2025 Annual Meeting, designed to enhance and shorten the radiation therapy workflow. Integrated within the Edison digital ecosystem, the innovation reflects GE HealthCare’s broader strategy to embed AI across imaging and clinical operations, although not specifically focused on automated radiology report generation.
In June 2024, RADPAIR, a leader in healthcare technology, and RamSoft®, a leader in cloud-based RIS/PACS radiology solutions, announced that AI-driven radiology report generation has been integrated into the OmegaAI® platform. Combining RADPAIR's state-of-the-art Gen AI platform for automated report generation with RamSoft's, OmegaAI PACS/RIS/VMA platform significantly advances AI-driven enterprise imaging. As these solutions have no footprint, viewing and reporting of images can be done through a single browser-based interface. The same integration between RamSoft's PowerServerTM platform and RADPAIR's AI report generation application will soon be made available by the parties.
Aidoc Medical Ltd.
Enlitic, Inc.
Nuance Communications, Inc.
Siemens Healthineers AG
Ge Healthcare
| Report Metric | Details |
|---|---|
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Companies |
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By Technology
Natural Language Processing (NLP)
Machine Learning
Deep Learning
Computer Vision
Others
By Application
MRI Scan Report Generation
CT Scan Report Generation
X-Ray Report Generation
Ultrasound Report Generation
Mammography Report Generation
Others
By End-User
Hospitals And Clinics
Diagnostic Imaging Centers
Research Institutes And Academic Centers
Others
By Geography
North America
United States
Canada
Mexico
South America
Brazil
Argentina
Others
Europe
United Kingdom
Germany
France
Italy
Spain
Others
Middle East and Africa
Saudi Arabia
UAE
Others
Asia Pacific
Japan
China
India
South Korea
Indonesia
Taiwan
Others