Radiology AI Market

The report "Radiology AI Market by Offering (On-Device, SaaS), Function (Triage, Workflow, CDSS, Acquisition, Processing, Reporting), Modality (CT, MRI, X-ray), Indication (Onco, Cardio, Neuro), End User (Hospital, Imaging Center), Region - Global Forecast to 2030", is projected to reach USD 2.27 billion by 2030 from USD 0.76 billion in 2025, at a CAGR of 24.5%.

Browse 150 market data Tables and 50 Figures spread through 450 Pages and in-depth TOC on "Radiology AI Market by Offering (On-Device, SaaS), Function (Triage, Workflow, CDSS, Acquisition, Processing, Reporting), Modality (CT, MRI, X-ray), Indication (Onco, Cardio, Neuro), End User (Hospital, Imaging Center), Region - Global Forecast to 2030"
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The adoption of artificial intelligence in radiology is accelerating due to the urgent need to reduce diagnostic turnaround times and alleviate radiologist workload amid growing imaging complexity. AI-driven decision-support tools are enabling earlier disease detection by highlighting subtle abnormalities that may be missed during manual review, particularly in high-volume modalities such as CT, MRI, and digital pathology integration. Hospitals are increasingly prioritizing workflow automation to optimize image triage, modality scheduling, and report standardization, ensuring seamless coordination across Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS). Enterprise-level demand is rising for secure AI models that support multi-site image sharing and collaborative interpretation, strengthening clinical efficiency in networked hospital systems. The expansion of precision medicine initiatives is further supporting AI-enabled tumor characterization and disease progression tracking, driving personalized treatment decisions. Additionally, payers and providers are exploring value-based frameworks that reward AI-supported reductions in misdiagnosis rates, repeat scans, and unnecessary procedures.

The oncology segment is expected to record a significant CAGR in the radiology AI market, by indication.

Based on indication, the radiology AI market is segmented into oncology, cardiology, neurology, pulmonology/respiratory diseases, orthopedics, women’s health, and other indications. The oncology segment is expected to register the highest CAGR in the radiology AI market, driven by the rapidly increasing global cancer burden and the significant dependence on imaging for cancer detection, staging, treatment planning, and ongoing surveillance. For instance, in January 2024, the American Cancer Society projected that the US witnessed approximately 2,001,140 new cancer cases and 611,720 cancer deaths. AI tools offer significant value in oncology by enabling early and precise lesion detection, automating tumor segmentation and quantification, and enhancing therapy response evaluation. High imaging volume in cancers such as breast, lung, prostate, and colorectal further accelerates adoption. Additionally, oncology-focused AI solutions benefit from strong regulatory momentum, growing commercial availability, and continued investment from healthcare providers and life science organizations seeking to improve diagnostic efficiency and patient outcomes. As a result, oncology remains the fastest-growing clinical application area in the global radiology AI market.

The hospitals segment accounted for a significant share of the radiology AI market, by end user, in 2025.

Based on end user, the radiology AI market is segmented into hospitals, diagnostic imaging centers, and others. In 2025, the hospitals segment accounted for a significant market share in the radiology AI market, driven by the high volume of imaging procedures conducted in hospital settings, strong investments in digital infrastructure, and the increasing prioritization of AI integration to enhance diagnostic accuracy and workflow efficiency. Hospitals are rapidly adopting AI-powered imaging platforms for applications such as triaging, image reconstruction, and decision support, supported by enterprise-level PACS/VNA systems and EHR interoperability. Moreover, hospital systems often serve as early adopters for AI vendors due to their larger budgets, the need for multi-specialty integration, and a focus on improving patient outcomes and operational efficiency.

Asia Pacific is expected to register a significant CAGR during the forecast period.

The Asia Pacific market is projected to register considerable market growth during the forecast period, driven by the expansion of market players in emerging economies such as China, India, and Southeast Asian countries. Growing awareness about AI-driven diagnostic tools and advanced imaging systems is expected to fuel adoption in hospitals, imaging centers, and research institutions. According to UN statistics, over 33% of the Japanese population is aged 60 years and above, and Asia is projected to see a sharp rise in its elderly population, reaching 21% by 2060. The aging population is associated with a higher prevalence of chronic diseases, increasing the demand for AI-powered radiology solutions that enhance diagnostic accuracy and efficiency.

Additionally, increased government investments in healthcare infrastructure in countries such as China, India, and Thailand are creating opportunities for radiology AI solution providers to expand their footprint in the region. For instance, Singapore’s National AI Strategy 2023 allocated a budget of USD 743 million. The initiative aims to address demographic challenges stemming from a rapidly aging population, with 24% of Singapore’s population expected to be over 65 by 2030. These AI technologies are being applied across healthcare, including medical imaging and diagnostics, where they enhance the speed and accuracy of disease detection through analysis of X-rays, CT scans, and MRIs.

Key Market Players

The key players in radiology AI market include: Siemens Healthineers AG (Germany), Microsoft (US), Koninklijke Philips N.V. (Netherlands), GE HealthCare (US), Fujifilm Holdings Corporation (Japan), Canon Medical Systems Corporation (Japan), Merative (US), DeepHealth (RadNet, Inc.) (US), Shanghai United Imaging Healthcare Co., LTD (China),  Hologic, Inc. (US), and Enlitic, Inc. (US), among others.

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