Radiology AI Market worth $2.27 billion by 2030 with 24.5% CAGR | MarketsandMarkets™
DELRAY BEACH, Fla., Nov. 20, 2025 /PRNewswire/ -- The global Radiology AI Market, valued at US$0.61 billion in 2024, stood at US$0.76 billion in 2025 and is projected to advance at a resilient CAGR of 24.5% from 2025 to 2030, culminating in a forecasted valuation of US$2.27 billion by the end of the period. The steady market growth is driven by the rising imaging volumes, need for advanced diagnostic imaging, workflow automation, and early disease detection. The increasing integration of AI into radiology systems enables clinicians to analyze large imaging datasets with higher accuracy and speed, thereby improving patient outcomes and enhancing clinical efficiency. The accelerated regulatory clearances for radiology AI tools, the growing burden of chronic diseases, the expanding use of imaging modalities, and the shortage of skilled radiologists further reinforce the demand for AI-enabled diagnostic tools.
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By 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.
By 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.
By geography, 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.
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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.
GE Healthcare
GE HealthCare is one of the leading players in the global radiology AI market, leveraging its strong imaging portfolio and AI-based platforms to enhance precision diagnostics. The company's Edison platform serves as the foundation for its AI-driven solutions, integrating machine learning algorithms into medical imaging workflows. The AIR Recon DL, a deep learning-based image reconstruction technology, significantly improves image clarity and reduces scan time across MRI systems. Similarly, its Critical Care Suite 2.0 uses AI to detect pneumothorax in chest X-rays, providing on-device analysis directly at the point of care.
GE HealthCare continues to expand its AI ecosystem through collaborations with NVIDIA, Amazon Web Services (AWS), and deep-learning startups. The company's focus on interoperability allows radiologists to integrate AI seamlessly into existing PACS and RIS platforms, enhancing diagnostic efficiency. In 2024, GE launched Revolution Ascend CT with Effortless Workflow, combining AI-driven automation with advanced imaging capabilities. The company's strong presence across developed and emerging markets, combined with continuous innovation and clinical validation, positions it as a frontrunner in operational AI and precision imaging.
Siemens Healthineers AG
Siemens Healthineers is one of the most prominent players in radiology AI, offering an extensive suite of AI-enabled imaging and workflow solutions under its AI-Rad Companion and syngo.via platforms. The AI-Rad Companion portfolio covers multiple body regions, including the brain, chest, prostate, and spine, helping radiologists automatically quantify and highlight clinically relevant features in imaging scans. Siemens also integrates AI into its advanced imaging systems, such as MAGNETOM Free.Max MRI and SOMATOM Definition Edge CT to improve image reconstruction, reduce scan duration, and enhance diagnostic accuracy.
In 2024, Siemens Healthineers launched AI-Pathway Companion, a decision-support system that connects imaging data with clinical, molecular, and laboratory information to enable precision oncology and personalized treatment planning. The company's Digital Twin initiatives and collaboration with Microsoft for AI-based healthcare cloud infrastructure further enhance its position in the global market. With a strong focus on digital transformation, automation, and multi-modality integration, Siemens Healthineers continues to shape the future of radiology by bridging imaging intelligence with clinical decision-making.
Koninklijke Philips N.V.
Koninklijke Philips N.V. holds a strong and diversified position in the radiology AI market, leveraging its broad imaging portfolio and deep informatics expertise supported by over 20 FDA-cleared Radiology AI solutions in the US (2018–2022). Through its Diagnosis & Treatment segment, Philips integrates AI across CT, MR, and ultrasound systems to enhance precision diagnosis and streamline workflows. Its Philips AI Manager provides radiology departments with a cloud-based ecosystem of AI applications, enabling enhanced image analysis and workflow efficiency. Key innovations include Precise Image and Precise Position for CT, SmartSpeed for accelerated MRI, and the Advanced Visualization Workspace for integrated AI-powered diagnostics. Strategic partnerships, notably with Nvidia, aim to develop foundational AI models for MRI, improving scan speed, image quality, and operational efficiency.
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