AI in Pathology Market Size & Outlook, 2026-2034

AI in Pathology Market Size

The AI in pathology market was valued at USD 166.41 million in 2025 and is estimated to reach USD 1,140.55 million by 2034, growing at a CAGR of 23.8% during the forecast period (2026-2034). AI in pathology. AI tools in pathology are used by pathologists to automate routine tasks through enhanced diagnostic accuracy and consistency.

Key Market Insights

• North America dominated the AI in pathology market with the largest market share of 41.29% in 2025.
• Asia Pacific is expected to be the fastest-growing region in the AI in pathology market during the forecast period at a CAGR of 25.69%.
• By offering, the softwaresegment dominated the market with the largest share of 08% in 2025.
• By technology, the computer vision-based image analysis segment is expected to grow rapidly during the forecast period at a CAGR of 17%.
• By application, the drug discovery segment is projected to grow at a CAGR of 24.42% during the forecast period.
• By end use, the hospital & reference laboratories segment is expected to grow at a CAGR of 24.71% between 2026 and 2034.
• The US AI in pathology market size was valued at USD 60.54 million in 2025 and is projected to reach USD 77.36 million in 2026.

AI in Pathology Market Trends

Integration of multi-omics pathology AI platforms to bridge radiomics with genomics

The convergence of multi-omics information with pathology imaging is a major trend in the market. Sophisticated AI platforms integrate images with genomic, transcriptomic, and proteomic information to provide enhanced disease characterization. This multimodal AI platform improves the accuracy of complex disease identification and provides treatment options beyond the capabilities of traditional image analysis platforms.

Adoption of federated learning for collaborative AI models

The use of federated learning to build AI models in different hospitals without exchanging patient data is another trend that is contributing to the growth of the market. For instance, organizations such as Owkin are applying this technique to train pathology models on distributed data sets. This trend helps in complying with regulations, improving collaboration, and speeding up the development of AI models that are clinically valid.

AI in Pathology Market Drivers

Rising adoption of digital pathology to address pathologist shortages drives market growth

The increasing use of digital pathology solutions to address the rising number of cases and the shortage of qualified pathologists boosts market growth. There is a disparity between the rising volume of cases and the number of qualified pathologists. The American Society for Clinical Pathology reports that only 600 new pathologists enter the healthcare sector every year, which is far below the required number of 700 to 840. Therefore, healthcare organizations are adopting digital slide scanning and AI solutions to automate mundane tasks, decrease turnaround times, and enhance the accuracy of diagnoses. This development has increased efficiency in labs and paved the way for AI adoption in practice.

Collaborations between biopharma and AI solution providers boosts market

Biopharma companies collaborate with AI solution providers to speed up target identification, automate image analysis, and translate pathology analysis from the vast amount of image data generated during preclinical and clinical studies. AI in pathology tools assists biopharma companies in standardizing scoring, reducing variability, and quantifying biomarkers for consistent, scalable readouts. AI models are trained to study patterns in large datasets, which help biopharma companies to discover new biomarkers and develop companion diagnostics. Such collaborations improve clinical efficiency, accelerate innovations using real-world evidence, and build solutions around diagnostics.

Market Restraints

Interoperability challenges across diverse pathology imaging systems restrains market

The low level of interoperability between AI software and whole slide imaging scanners is hampering the adoption of digital tools. Pathology labs use scanners from different companies, and AI algorithms that are trained on a particular image type do not perform well on others. For instance, research studies published in various peer-reviewed journals have found inconsistencies in the accuracy of AI algorithms when used on different brands of scanners.

Market Opportunities

Commercialization via regulatory approvals offers scalable growth opportunities

Regulatory approval enables the use of AI platforms for primary diagnosis purposes and not just for research purposes. This builds trust in AI platforms and takes them from being pilot projects to viable, scalable, enterprise-ready tools. Regulatory clearance also helps in validating performance and complying with legal aspects of medical devices. Thus, commercialization via approvals from regulatory authorities drives adoption by reference labs and diagnostics clinics. For example, PathAI’s AISight Dx platform has been approved by the FDA and uses a structured framework that allows for system enhancement without the need for a full regulatory review. This makes it easier to implement and helps build trust among healthcare professionals.

Technological Landscape

• Paige is an AI pathology platform that uses deep learning for cancer detection and tissue analysis.
• AISight is a cloud native image management platform used for biomarker quantification, anomaly detection, and clinical diagnostics.
• Concentriq integrates AI-powered image analysis, collaboration tools, and data management for enhanced digital workflows in labs.  

Regional Analysis

The AI in pathology market in North America held a market share of 41.29% in 2025, which was supported by large-scale pathology digitization. For instance, the Mayo Clinic has scanned over 12 million glass slides and holds an archive of over 25 million samples. This digitization effort creates a resource for training AI models and the rapid adoption of AI pathology solutions in regional healthcare systems. The region also has a robust healthcare infrastructure and a willingness to adopt AI models.

The US dominated the region with major AI in the pathology market share, due to the early adoption of AI platforms by major clinical laboratories. For instance, PathAI’s AISight is used by over a dozen leading anatomic pathology labs to analyze complex cancer biomarkers in real patient samples. This deployment improves diagnostic precision and accelerates clinical integration across US healthcare systems.

Asia Pacific

The Asia Pacific market is expected to grow at a CAGR of 25.69% during the forecast period, owing to the implementation of AI-integrated digital pathology platforms in major regional hospitals. For instance, the Kameda Medical Center in Japan is digitizing workflows to enable remote tissue image review and improve diagnostic collaboration and operational efficiency.

China dominated the market in Asia Pacific due to the increasing burden of diseases, the structural shortage of trained pathologists outside urban areas, and strong government backing for AI adoption. The country is facing a high incidence of cancer, projected to reach 3.2 million by 2030 in older adults, as per PubMed. This will also lead to increasing diagnostic volume wherein AI can accelerate identification and validation on large datasets. Shortage of pathologists will also lead to higher demand of AI in pathology to streamline pre-screening and quality control outside Tier I cities. National health strategies, such as the Healthy China 2030 Plan, support the adoption of AI in healthcare facilities. 

Europe

The Europe AI in pathology market is driven by higher clinical adoption of AI tools. For instance, Aiforia’s algorithms are used in routine diagnostic workflows at major French and Swedish hospitals. The adoption of AI tools assists prostate, breast, and other cancer analyses, improving diagnostic consistency. Digital health initiatives such as the EU Cancer Plan & European Health Data Space promote digital health infrastructure and cross-border data sharing. The CE-IVDR also provides clear regulations for AI-based solutions, which encourage companies to develop clinically validated AI in pathology tools.

Germany leads the Europe region due to an aging population, higher adoption of digital pathology, and a strong R&D ecosystem. It is projected that by 2030, 1 in 4 Germans will be over 60 years of age, which will increase disease burden as well as pathology workload. The country is one of the highest adopters of whole-slide imaging in the region, with integrated imaging systems in hospitals for tumor detection, biomarker quantification, and workflow automation. The country also boasts of a strong R&D ecosystem with a mix of academia, biotech, and MedTech startups.

Latin America

The Latin America AI in pathology market growth is augmented by increasing investments by established players, such as PathAI’s investment in Rede D’Or (Brazil) and Aiforia’s investments in private hospitals of Chile and Mexico. Countries in this region are also promoting digital AI healthcare tools, which reduce adoption barriers and gives boosts to pilot projects. The region has active oncology research programs, which need AI support for clinical validation and research-grade analysis. Thus, an encouraging research ecosystem and investments in AI tool integration are expected to boost the Latin American market.

Argentina is expected to lead the AI in pathology market in Latin America. The country has deployed platforms such as Digpatho from Córdoba, which aids rapid and consistent breast cancer detection. Active oncology research groups such as GAICO (Grupo Argentino de Investigación Clínica en Oncología) also use AI for translation research in cancer. Hospitals and private diagnostic centers are digitizing pathology operations for faster diagnosis and treatment guidance.

Middle East and Africa

The Middle East and Africa AI in pathology market is growing at a steady pace due to factors such as higher cancer incidence, a shortage of qualified professionals, and favorable government initiatives. According to Globocan 2025, the region is expected to see over 1 million new cancer cases annually due to aging populations and lifestyle changes. Thus, higher diagnostic demand will lead to higher adoption of AI in pathology for accurate and timely diagnosis. The region is facing a critical shortage of trained and seasoned pathologists, which increases dependence on AI in pathology tools to overcome diagnostic bottlenecks. Favorable government initiatives such as Vision 2030 and the UAE National AI Strategy encourage AI in healthcare and research with support in terms of funding, incentives, and policies.

The South African market is overseeing increasing healthcare demand, digital adoption, and investments in upgrading infrastructure. The country is expanding its AI integration into hospitals for remote consultation in underserved areas and reducing pathology workload. The government supports the deployment of AI and digital pathology through pilot projects in urban areas under the Pan-African Telepathology & AI Networks initiative. Global market players, such as Philips and Paige, have also entered South Africa, which will boost the deployment of cloud-based AI tools in healthcare.

Offering Insights

The software segment accounted for the largest AI in pathology market share in 2025, as it reduces workload, interprets complex data, and simplifies lab operations. Additionally, advanced software that can detect tissue anomalies is increasingly used by academic and research organizations to speed up the research process, which, in turn, boosts the demand for software and supports segment growth.

The hardware segment is projected to be the fastest-growing segment with a CAGR of 25.16% during the forecast timeframe. Growth is propelled by the rising demand for high-resolution digital pathology scanners. These scanners provide clearer images, faster processing, and support AI analysis. Due to these advantages, hospitals and laboratories are increasingly adopting hardware for diagnostic imaging.

Technology Insights

The machine learning segment dominated the market, with a considerable share of 44.86% in 2025. Machine learning is increasingly used to address soaring diagnostic workloads and reduce inter-observer variability. Machine learning automates cell counting and tumor quantification in complex diagnosis processes, which ensures its stable demand and reinforces the dominance of the segment.

The computer vision-based image analysis segment is projected to grow at the fastest pace with a CAGR of 24.17% during 2026-2034. This growth is stimulated due to the use of AI models for automation of the quantification of histopathological features, such as nuclear morphology, which were time-consuming for humans to quantify. These vision algorithms enhance the detection of rare cancers and biomarkers, improving diagnostic consistency and accelerating research in oncology.

Application Insights

The disease diagnosis & prognosis segment dominated the market in 2025 because AI pathology tools show high diagnostic accuracy in clinical studies, with a sensitivity of about 96.3% and specificity of 93.3% when applied to whole slide images across various diseases.

The drug discovery segment is projected to grow at a CAGR of 24.42% during the forecast timeframe, as these tools help identify therapeutic targets and biomarker discovery. These capabilities help researchers analyze large pathology datasets in preclinical research. Thus, all aforementioned factors support the segment growth.

End Use Insights

The pharmaceutical & biotechnology companies segment dominated the market in 2025, because they use AI for accelerated drug discovery to analyze a high volume of tissue samples rapidly. They also utilize biomarker identification for precise and personalized therapies by using integrated solutions.

The hospital & reference laboratories segment is projected to grow at a CAGR of 24.71% during 2026-2034. These facilities handle the largest volume of pathology cases, which leads to increased AI adoption for faster and precise processing of samples.

Figure: AI in Pathology Market Segments

Regulatory Bodies Governing AI in the Pathology Market

Competitive Landscape

The market is moderately competitive, with established digital pathology and AI solution providers holding substantial AI in the pathology market share. Leading players such as PathAI, Paige AI, and Roche Diagnostics dominate through advanced technology platforms, extensive clinical collaborations, and strong regulatory compliance. These companies focus on product innovations, partnerships with hospitals and laboratories, and strategic integration to enhance market presence.

List of Key and Emerging Players in AI in Pathology Market

1. Koninklijke Philips N.V.
2. AstraZeneca
3. Tribun Health
4. Hologic, Inc.
5. Proscia, Inc.
6. Fujifilm
7. Akoya Biosciences, Inc.
8. Indica Labs Inc.
9. Tempus Labs, Inc.
10. Ibex Medical Analytics Ltd.
11. Paige AI, Inc.
12. Aiosyn
13. PathAI
14. Deep Bio Inc.
15. AIRA Matrix Private Limited
16. Lumea Inc.
17. Techcyte, Inc.
18. Mindpeak GmbH
19. QritiveOptraScan, Inc.
20. Owkin, Inc.
21. Ibex Medical Analytics
22. Aiforia

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Source: Secondary Research