AI in Breast Imaging Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2021-2031

The Global AI In Breast Imaging Market is projected to expand from USD 320.32 Million in 2025 to USD 440.92 Million by 2031, registering a CAGR of 5.47%. This sector involves the application of machine learning and deep learning algorithms to aid radiologists in analyzing medical imagery, including mammograms, ultrasound, and MRI scans, for enhanced anomaly detection. Growth is primarily driven by the increasing global prevalence of breast cancer, which necessitates robust screening programs, and the critical need to alleviate the workload of overburdened radiologists. By automating routine tasks and prioritizing suspicious cases, these tools address the disparity between surging image volumes and the limited availability of specialists, thereby improving clinical workflow efficiency.

This demand for operational support is evident in the rising utilization of these technologies among practitioners. In 2024, the European Society of Radiology reported that 48% of surveyed members were currently using AI, with the technology expected to have the most significant impact on breast and oncologic imaging. However, a major challenge hindering market expansion is the high cost associated with implementation and integration into existing systems. These financial barriers, often compounded by complex regulatory requirements, prevent resource-constrained healthcare facilities from adopting these diagnostic solutions, effectively restricting broader market penetration.

Market Drivers

The growing shortage of radiologists combined with an increasing diagnostic workload serves as the most urgent catalyst for AI adoption in the breast imaging sector. Healthcare systems globally face a critical imbalance where the volume of imaging studies exceeds the available workforce, resulting in burnout and diagnostic delays. AI solutions are consequently being integrated to triage scans and automate reporting, acting as a force multiplier for strained departments. The Royal College of Radiologists noted in their 'Clinical Radiology Census 2023 Report' in June 2024 that the UK healthcare system faces a 30% shortfall of clinical radiologists, which is projected to worsen to 40% by 2028. This scarcity has accelerated commercialization efforts; Axis Imaging News reported in May 2024 that the U.S. FDA added 191 new AI-enabled medical devices to its approved list, with 128 focused on radiology, highlighting the industry's aggressive response to workforce limitations.

Concurrently, the increasing global incidence of breast cancer necessitates more robust screening protocols, further amplifying the need for efficient technologies. As screening programs expand to catch disease earlier, the number of mammograms requiring interpretation is surging, placing immense pressure on diagnostic infrastructure to maintain accuracy and throughput. According to the American Cancer Society's 'Breast Cancer Facts & Figures 2024-2025' released in January 2024, an estimated 310,720 new invasive breast cancer cases are projected to be diagnosed in women in the US during 2024. This escalating prevalence drives the deployment of AI algorithms capable of flagging high-risk anomalies, ensuring that rising case volumes do not result in missed diagnoses or delayed treatments.

Market Challenges

The high cost of implementation and integration constitutes a substantial impediment to the expansion of the global AI in breast imaging market. Deploying these advanced diagnostic tools requires significant capital investment, covering the acquisition of sophisticated software, necessary hardware upgrades, and complex IT infrastructure integration. Beyond the initial outlay, healthcare facilities face ongoing expenses for system maintenance, regular software updates, and specialized staff training. For many organizations, particularly smaller independent practices and resource-constrained clinics, these financial demands are prohibitive, especially given the current lack of comprehensive reimbursement models to ensure a clear return on investment.

This financial strain is a primary reason for the hesitation observed across the industry. According to the European Society of Radiology in 2024, 49.5% of surveyed members identified costs or lack of budget as the main potential barrier to AI implementation in clinical practice. Consequently, market growth remains skewed toward well-funded academic centers, while broader adoption across the general healthcare landscape is stalled. This economic disparity effectively limits the market's reach and decelerates the overall trajectory of global industry expansion.

Market Trends

The proliferation of AI solutions for Digital Breast Tomosynthesis is addressing the complexities of analyzing volumetric imaging data. As 3D mammography generates larger datasets than traditional 2D modalities, AI algorithms are increasingly deployed to enhance lesion conspicuity and reduce false negatives, particularly in dense breast tissue. This efficacy was substantiated by recent large-scale clinical data; RadNet Inc. reported in a November 2025 press release regarding the 'Landmark Nature Health Study Demonstrates the Effectiveness of DeepHealth's Novel AI-Powered Breast Cancer Detection Workflow' that an evaluation involving over 579,000 women revealed their AI-supported screening protocol achieved a 21.6% increase in the cancer detection rate compared to standard 3D mammography.

Simultaneously, strategic alliances between AI vendors and imaging OEMs are accelerating market penetration by embedding analytics directly into radiology reading environments. These collaborations allow healthcare providers to access advanced diagnostic tools within their existing infrastructure rather than investing in fragmented, standalone software solutions. A notable instance involves major institutions securing comprehensive access to such technologies; Radiology Business reported in April 2025 in the article 'Big-name healthcare orgs tap AI to improve breast imaging workflows' that Therapixel’s partnership to integrate its MammoScreen software at Mayo Clinic increased radiologist interpretation speeds by approximately 35%, underscoring the operational value driving these commercial agreements.

Key Players Profiled in the AI In Breast Imaging Market

• Visage Imaging, Inc.
• CureMetrix, Inc.
• DeepHealth, Inc.
• GE HealthCare Technologies Inc.
• Hologic, Inc.
• Siemens Healthineers AG
• Fujifilm Holdings Corporation
• Koninklijke Philips N.V.
• iCAD, Inc.
• Medicalgorithmics SA

Report Scope

In this report, the Global AI In Breast Imaging Market has been segmented into the following categories:

AI In Breast Imaging Market, by Component:

• Hardware
• Software

AI In Breast Imaging Market, by Imaging Modality:

• Mammography
• Ultrasound Imaging
• MRI

AI In Breast Imaging Market, by Application:

• Screening
• Diagnostics
• Image-guided Biopsy

AI In Breast Imaging Market, by End Use:

• Hospitals & Clinics
• Diagnostic Imaging Centers
• Research Institutes

AI In Breast Imaging Market, by Region:

• North America
• Europe
• Asia-Pacific
• South America
• Middle East & Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI In Breast Imaging Market.

Available Customization

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• Detailed analysis and profiling of additional market players (up to five).

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