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病理學領域的人工智慧（AI）：市場洞察、競爭格局和市場預測（2034 年）

Artificial Intelligence (AI) in Pathology - Market Insights, Competitive Landscape, and Market Forecast - 2034

出版日期: 2026年07月01日 | 出版商:

DelveInsight | 英文 150 Pages | 商品交期: 2-10個工作天內

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簡介目錄圖表

病理學人工智慧（AI）市場概述

概述：

2025年病理學人工智慧（AI）市場規模估計為1.3億美元，預計到2034年將達到9.5億美元。這一成長是由全球癌症患者數量的增加、病理學家短缺問題的日益嚴重以及FDA已通過核准的AI軟體的出現所推動的，這些軟體可以自動對數位化切片進行癌症檢測、分期和生物標記定量分析。
全球病理學人工智慧（AI）市場預計在 2026 年至 2034 年的預測期內將以 24.7% 的複合年成長率成長。
以產品細分市場來看，預計到 2025 年，軟體細分市場將佔 51% 的佔有率，從而推動病理學領域的人工智慧 (AI) 市場發展。
按技術分類，預計到 2025 年，機器學習領域將佔 45% 的市場佔有率，引領病理學領域的人工智慧 (AI) 市場。
按應用領域分類，預計到 2025 年，疾病診斷領域將佔市場佔有率的 58%，引領病理學領域的人工智慧 (AI) 市場。
按最終用戶分類，醫院和實驗室領域在 2025 年引領市場，佔病理學人工智慧 (AI) 市場的 47% 佔有率。
預計到 2025 年，北美將佔據 41% 的市場佔有率，推動全球病理學人工智慧 (AI) 市場的銷售，並在全球範圍內佔據最高的市場佔有率。

病理學中的人工智慧（AI）是指將機器學習、深度學習和電腦視覺應用於數位化組織和細胞學標本，以輔助疾病的檢體、分級、量化和解讀。基於全切片成像掃描儀和影像管理系統等數位病理基礎設施，AI演算法分析高解析度切片影像，以識別可疑病變、對免疫組化和生物標記進行評分、量化腫瘤特徵、支持伴隨診斷，並透過病例分診、品管和數位化報告最佳化工作流程。該市場結合了軟體（例如演算法和影像管理平台）、硬體（包括掃描器和運算基礎設施）以及從部署和整合到託管分析的各種服務。核心技術包括卷積類神經網路和其他神經網路、電腦視覺以及基於數百萬張切片訓練的新興生成模型和基礎模型。其應用範圍涵蓋腫瘤和非腫瘤疾病的解剖病理學、伴隨診斷、遠端病理學、生物標記主導的精準醫療和藥物研發。在包括 FDA 批准、歐盟 IVDR 認證、大規模基礎模型的引入以及行業重組在內的一系列發展推動下，人工智慧正在成為現代病理學中最具變革性的力量，將該領域從以玻片為中心的診斷轉變為以電腦驅動、數據驅動的診斷。

病理學人工智慧市場的主要市場促進因素

全球癌症負擔日益加重，導致切片檢查和切片處理量不斷增加。國際癌症研究機構 (IARC) 預測，癌症患者人數將從 2022 年的 2,000 萬人增加到 2050 年的 3,500 萬人。
全球病理學家短缺問題日益嚴重，加上病例數量不斷增加，推動了人工智慧在自動化檢測、分級和量化方面的應用，從而提高了處理能力和一致性。
法規核准速度的加快提升了臨床實務的信心。預計到2025年，獲得FDA批准的AI病理診斷產品數量將達到10種，歐盟體外診斷醫療器材法規（IVDR）認證也在擴大市場進入。
從玻璃載玻片到數位病理學和全載玻片成像的轉變，正在創建一個資料基礎設施，使人工智慧演算法運作。
基於數百萬張幻燈片訓練的基礎模型和生成式人工智慧輔助駕駛技術的出現，正在擴展癌症檢測、生物標記發現和報告生成等領域的能力。
對精準腫瘤學、伴隨診斷和生物標記定量分析日益成長的需求，正在推動製藥業和臨床實踐中採用人工智慧病理學。
預計到 2034 年，癌症負擔、人才短缺、數位化、監管支持以及基礎模型的整合將推動市場持續快速成長。

推動病理學人工智慧（AI）市場成長的因素

市場促進因素

全球癌症負擔日益加重，以及切片數量的增加

病理學領域人工智慧（AI）市場最強勁的驅動力是全球癌症負擔的日益惡化。這導致切片檢查和切片的工作量增加，診斷難度也隨之增加。根據國際癌症研究機構（IARC）的數據，2022年全球新增癌症病例2,000萬例，預計2050年將達到3,500萬例。常見惡性腫瘤（如前列腺癌）的發生率預計也將急劇上升，到2040年，全球前列腺癌病例數預計將增加一倍。每次癌症檢查都會產生組織樣本和細胞學切片，這些都需要檢查、分級和表徵。此外，在精準腫瘤學和伴隨診斷的工作流程中，還需要進行生物標記和免疫組化評分。病理學領域的人工智慧（AI）能夠快速、一致地檢測可疑病變、進行腫瘤分級和生物標記定量，從而直接應對日益成長的工作量。隨著癌症發生率上升和診斷複雜性增加，對人工智慧輔助病理學家工作的需求將會成長，從而推動市場成長至 2034 年。

病理學家短缺問題日益嚴重，病例數也不斷增加。

全球病理學家短缺問題日益嚴重，加之病例數量不斷增加，是推動人工智慧應用的主要動力。訓練有素的病理學家數量成長速度遠低於需求，導致檢測積壓、報告時間延長、職業倦怠以及觀察觀察增加。在大型學術機構以外的地區和資源匱乏地區，病理學家短缺問題尤其突出。病理學領域的人工智慧可以透過自動化重複性檢測和測量任務、病例分診、撰寫定量分析報告以及作為診斷安全網識別病理學家經常忽略的微小和罕見癌症，來緩解這一缺口。人工智慧無需相應增加人員配置，即可提高處理能力、一致性和可及性，從而為處理病例量最大的醫院和實驗室帶來顯著的營運價值。這種結構性的勞動力短缺壓力將在整個預測期內推動臨床機構和實驗室對人工智慧輔助操作的需求。

市場限制因素

儘管人工智慧（AI）在病理領域的市場發展勢頭強勁，但仍面臨許多限制因素。向數位化和AI驅動的病理學轉型需要全切片成像掃描儀、儲存和計算基礎設施，以及與實驗室系統的整合，所有這些都意味著大量的資金投入，對於資源有限的小規模檢查室而言成本高昂。監管和臨床檢驗要求也日益複雜。 AI診斷工具必須展現出明確的臨床療效，並符合不斷演變的FDA和歐盟體外醫療設備法規（IVDR）框架，這導致開發週期延長，並需要持續進行上市後性能監測。能夠開發、檢驗和操作AI系統的專業人員短缺，阻礙了AI技術的應用，調查顯示，大多數機構都難以招募合格的AI人才。掃描器、影像格式和AI平台之間互通性和標準化方面的差距，使得整合和可重複性變得複雜，而專有格式的持續存在則阻礙了可擴展性。演算法偏差、在不同人群中的普遍適用性以及人工智慧診斷的課責等問題，都要求提高透明度並進行嚴格的檢驗，這使得臨床醫生的信任成為一個持續存在的障礙。不同地區對人工智慧病理診斷的保險報銷仍然不均衡且不成熟，限制了投資回報。同時，與大規模切片資料集相關的資料隱私、管治和網路安全義務也構成了負擔。儘管癌症負擔、人才短缺和數位化等潛在促進因素依然強勁，但這些障礙——資金、監管、人才、互通性、信任和保險報銷——共同減緩了人工智慧技術的發展速度。

可以從以下幾個方面評估競爭格局：

市場集中度：市場集中度適中，主要平台開發商和大型診斷製造商以及快速成長的專業新興企業均參與其中。
Tempus (Paige)、羅氏、飛利浦、PathAI 和 Ibex 等領先公司透過檢驗的平台和許可證為頂級企業提供支援。
地理擴張：領導企業擁有全球商業網路，建立的夥伴關係關係不僅涵蓋其國內網路，也擴展到歐洲、拉丁美洲和亞太地區。
產品系列優勢：領先公司擁有涵蓋影像管理、已通過核准的檢測和評級演算法以及生物標記分析的綜合產品組合。
管道優勢：我們在多組織檢測、預後和預測工具以及基礎模型方面擁有強大的管道，其中包括一個被指定為「突破性」的平台。
策略合作：人工智慧正透過廣泛的合作被整合到診斷和掃描儀中，例如羅氏與 PathAI 和 Ibex 的合作，以及徠卡生物系統與 Paige 的合作。
併購活動：以 Tempus 收購 Page 為首的產業重組正在進行中，目的是建立大規模的腫瘤基礎設施模式。
監管優勢：FDA 批准和歐盟 IVDR 認證是決定性的競爭優勢，預計到 2025 年批准數量將達到 10 個。
創新重點：基礎模式、生成式人工智慧輔助駕駛、多組織偵測、預後和預測生物標記以及雲端原生企業平台。

病理學人工智慧市場報告要點

對病理學領域人工智慧 (AI) 市場的當前規模（2025 年）進行分析，並進行 9 年市場預測（2026 年至 2034 年）。
過去三年發生的重大產品和技術開發、合併、收購、合作和合資企業。
一家在病理學領域主導全球人工智慧（AI）市場的領先公司。
病理學人工智慧（AI）市場為競爭者提供了各種機會。
哪些細分市場在2025年表現最佳？這些細分市場在2034年的表現又會如何？
目前哪些地區和國家在病理學人工智慧（AI）市場表現最佳？
企業應將精力集中在哪些地區或國家，以抓住病理學領域人工智慧（AI）市場的未來成長機會？

本報告《病理學中的人工智慧（AI）市場》的主要讀者可能會從這項研究中受益。

病理領域的人工智慧（AI）產品供應商
研究機構和顧問公司
病理學領域與人工智慧相關的組織、協會、論壇和其他相關團體
政府機構和公司
新創公司、創業投資、私募股權公司
銷售代理和公司在病理學領域處理人工智慧（AI）相關事宜

這適用於希望了解更多關於病理學人工智慧 (AI) 市場以及該市場最新技術趨勢的各種終端用戶。

常問問題：

Q1. 病理學領域人工智慧（AI）市場的成長率是多少？

預計從 2026 年到 2034 年的預測期內，病理學領域的人工智慧 (AI) 市場將以 24.7% 的複合年成長率成長。

Q2. 病理學領域人工智慧（AI）市場的市場規模有多大？

2025年，病理學領域的人工智慧（AI）市場規模估計為1.3億美元，預計到2034年將達到9.5億美元。

Q3. 哪個地區在病理學人工智慧（AI）市場中處於主導？

北美地區憑藉其先進的醫療保健基礎設施、數位病理學的高普及率、最活躍的FDA核准和指導環境、在基礎模型方面的領先地位以及龐大的AI病理學開發人員群體，預計將主導AI病理學市場，到2025年將佔全球銷售額的41%。亞太地區預計將成為預測期內成長最快的地區。

第四季：病理學領域人工智慧（AI）市場的主要促進因素是什麼？

推動這一趨勢的主要因素是全球癌症患者人數的不斷增加。國際癌症研究機構（IARC）預測，癌症患者人數將從2022年的2,000萬人增加到2050年的3,500萬人。其他促成因素包括：由於病例增加導致病理學家短缺問題日益嚴重；法規核准速度加快（預計到2025年美國食品藥品監督管理局（FDA）將批准10種新藥）；病理學從傳統玻片檢查向數位病理學的轉變；以及基礎模型和生成式人工智慧輔助駕駛技術的出現。

Q5. 病理學領域人工智慧（AI）市場的主要參與者有哪些公司？

主要參與者包括Tempus AI, Inc.（Paige）、羅氏製藥、皇家飛利浦、PathAI, Inc.、Ibex Medical Analytics Ltd.、Proscia Inc.、Indica Labs, Inc.、Aiforia Technologies Plc、Hologic, Inc.和Visiopharm A/S。此外，「競爭格局」部分中提到的其他活躍研發公司，以及Akoya Biosciences、Mindpeak和ArteraAI也被視為主要參與者。 Tempus（Paige）、羅氏、飛利浦、PathAI和Ibex憑藉著成熟的平台和法規核准，在業界處於領先地位。

病理學領域人工智慧 (AI) 的市場促進因素
- 全球癌症負擔日益加重，以及病例數不斷增加
- 病理學家短缺問題日益嚴重。
- 加速監理核准
- 向數位化病理學和基礎模型過渡
病理學人工智慧（AI）市場的市場限制與挑戰
- 巨額資金和基礎設施需求
- 與監管、檢驗和信任相關的障礙
- 互通性、人力資源和還款的差異
病理領域人工智慧（AI）市場機遇
- 基礎模型和生成式人工智慧副駕駛
- 新興市場和遠端病理診斷的擴展

第4章影響分析：人工智慧、地緣政治、貿易和經濟趨勢

第5章：監理分析

美國
歐洲
日本
中國

第6章：病理學領域的人工智慧（AI）市場：波特五力分析

供應商的議價能力
買方的議價能力
新進入者的威脅
替代品的威脅
競爭公司之間的競爭

第7章：病理學人工智慧（AI）市場評估

以規定形式
- 軟體
- 硬體
- 服務
透過技術
- 機器學習
- 深度學習
- 電腦視覺
- 生成模型與底層模型
- 其他
透過使用
- 疾病診斷與預後
- 藥物傳輸與開發
- 伴隨診斷
- 工作流程和品管
最終用戶
- 醫院和檢驗實驗室
- 診斷檢查室
- 製藥和生物技術公司
- 研究和學術機構
按地區
- 北美洲
- 歐洲
- 亞太地區
- 世界其他地區

第8章：病理學領域人工智慧（AI）市場的競爭格局

市場集中度與結構
競爭定位與市場佔有率分析（加值服務）

第9章：病理學人工智慧（AI）市場新創企業資金籌措和投資趨勢

第10章：病理學領域的人工智慧（AI）市場：公司概況和產品概況

Tempus AI, Inc.（Paige）
- 公司簡介
- 公司簡介
- 財務概覽
- 產品系列
- 策略舉措/熵
F. Hoffmann-La Roche Ltd
Koninklijke Philips NV
PathAI, Inc.
Ibex Medical Analytics Ltd.
Proscia Inc.
Indica Labs, Inc.
Aiforia Technologies Plc
Hologic, Inc.
Visiopharm A/S

第11章：KOL的觀點

第12章：專案式教學方法

第13章：關於 DelveInsight

第14章免責聲明與聯絡方式

簡介目錄圖表

Product Code: DIMDCL0937

AI in Pathology Market Summary

Overview:

The AI in Pathology market is estimated at USD 0.13 billion in 2025 and is projected to reach USD 0.95 billion by 2034. Growth is anchored in the rising global cancer burden, a worsening shortage of pathologists, and a wave of FDA-cleared AI software that automates cancer detection, grading, and biomarker quantification on digitized slides.
The global AI in Pathology market is growing at a CAGR of 24.7% during the forecast period from 2026 to 2034.
By offering, the software segment dominated the AI in Pathology market with a 51% share in 2025.
By technology, the machine learning segment dominated the AI in Pathology market with a 45% share in 2025.
By application, the disease diagnosis segment dominated the AI in Pathology market with a 58% share in 2025.
By end user, the hospitals and reference laboratories segment dominated the AI in Pathology market with a 47% share in 2025.
North America dominated the global AI in Pathology market revenue with a 41% share in 2025, representing the highest regional market share globally.

Artificial intelligence (AI) in pathology refers to the application of machine learning, deep learning, and computer vision to digitized tissue and cytology specimens to assist in the detection, grading, quantification, and interpretation of disease. Building on the digital-pathology foundation of whole-slide imaging scanners and image management systems, AI algorithms analyze high-resolution slide images to flag suspicious foci, score immunohistochemistry and biomarkers, quantify tumor features, support companion diagnostics, and optimize workflow through case triage, quality control, and digital reporting. The market combines software, including algorithms and image-management platforms, with hardware such as scanners and computing infrastructure, and services spanning deployment, integration, and managed analytics. Core technologies include convolutional and other neural networks, computer vision, and emerging generative and foundation models trained on millions of slides. Applications span anatomic pathology in oncology and non-oncologic disease, companion diagnostics, telepathology, biomarker-driven precision medicine, and pharmaceutical research. Accelerated by a wave of FDA authorizations, EU IVDR certifications, and large foundation-model and consolidation moves, AI has become the most transformative force in modern pathology, shifting the field from glass slides toward computational, data-driven diagnosis.

AI in Pathology Market Key Growth Drivers

The rising global cancer burden is increasing biopsy and slide volumes, with the International Agency for Research on Cancer projecting cancer cases to rise from 20 million in 2022 to 35 million by 2050.
A worsening global shortage of pathologists, combined with rising caseloads, is driving adoption of AI that automates detection, grading, and quantification to improve throughput and consistency.
Accelerating regulatory clearances are building clinical trust, with FDA authorizations for AI pathology rising to ten in 2025 and EU IVDR certifications expanding market access.
The transition from glass slides to digital pathology and whole-slide imaging is creating the data foundation on which AI algorithms operate at scale.
The emergence of foundation models and generative AI co-pilots, trained on millions of slides, is expanding capability across cancer detection, biomarker discovery, and reporting.
Growing demand for precision oncology, companion diagnostics, and biomarker quantification is driving pharmaceutical and clinical adoption of AI pathology.
The convergence of cancer burden, workforce shortage, digitization, regulatory support, and foundation models is expected to sustain rapid growth in the market through 2034.

Key Companies in AI in Pathology Market

The competitive landscape is led by the following active developers and providers:

Tempus AI, Inc. (Paige)
F. Hoffmann-La Roche Ltd
Koninklijke Philips N.V.
PathAI, Inc.
Ibex Medical Analytics Ltd.
Proscia Inc.
Indica Labs, Inc.
Aiforia Technologies Plc
Hologic, Inc.
Visiopharm A/S

Factors Contributing to the Growth of the AI in Pathology Market

Market Drivers

Rising Global Cancer Burden and Slide Volumes

The most powerful driver of the AI in Pathology market is the rising global cancer burden, which increases biopsy and slide volumes and the complexity of diagnosis. The International Agency for Research on Cancer recorded 20 million new cancer cases in 2022 and projects 35 million by 2050, and the incidence of common malignancies such as prostate cancer is expected to rise sharply, with global prostate cancer cases projected to double by 2040. Each cancer workup generates tissue and cytology slides that must be examined, graded, and characterized, and precision-oncology and companion-diagnostic workflows add biomarker and immunohistochemistry scoring. AI in pathology directly addresses this growing workload by detecting suspicious foci, grading tumors, and quantifying biomarkers with speed and consistency. As cancer incidence climbs and diagnostic complexity deepens, demand for AI that augments pathologists expands, anchoring market growth through 2034.

Worsening Shortage of Pathologists and Rising Caseloads

A worsening global shortage of pathologists, combined with rising caseloads, is a central driver of AI adoption. The supply of trained pathologists is growing far more slowly than demand, producing backlogs, longer turnaround times, burnout, and variability in interpretation, with shortages especially acute outside major academic centers and in lower-resource regions. AI in pathology mitigates this gap by automating repetitive detection and measurement tasks, triaging cases, generating draft quantification, and acting as a diagnostic safety net that flags small or rare cancers a pathologist might miss. By improving throughput, consistency, and access without proportionally increasing staffing, AI delivers clear operational value to hospitals and reference laboratories handling the largest case volumes. This structural workforce pressure reinforces demand for AI augmentation across clinical and reference settings throughout the forecast period.

Market Restraints

Despite strong momentum, the AI in Pathology market faces material constraints. High capital requirements are a significant barrier, as the transition to digital and AI-enabled pathology demands whole-slide imaging scanners, storage and computing infrastructure, and integration with laboratory systems, costs that are difficult for smaller and lower-resource laboratories to absorb. Regulatory and clinical-validation requirements add complexity, as AI diagnostic tools must demonstrate clear clinical benefit and navigate evolving FDA and EU IVDR frameworks, lengthening development timelines and requiring ongoing post-market performance monitoring. A shortage of skilled professionals able to develop, validate, and operate AI systems constrains deployment, with surveys indicating most organizations struggle to find qualified AI talent. Interoperability and standardization gaps between scanners, image formats, and AI platforms complicate integration and reproducibility, and the persistence of proprietary formats slows scalability. Clinician trust remains a gating factor, as concerns about algorithmic bias, generalizability across diverse populations, and accountability for AI-influenced diagnoses require transparency and robust validation. Reimbursement for AI-enabled pathology remains uneven and immature across geographies, constraining return on investment, while data-privacy, governance, and cybersecurity obligations involving large slide datasets add burden. Together, these capital, regulatory, workforce, interoperability, trust, and reimbursement barriers temper the pace of growth, even as the underlying drivers of cancer burden, workforce shortage, and digitization remain firmly intact.

AI in Pathology Market Segment Analysis

The AI in Pathology Market by Offering (Software, Hardware, Services), Technology (Machine Learning, Deep Learning, Computer Vision, Generative and Foundation Models, Others), Application (Disease Diagnosis and Prognosis, Drug Discovery and Development, Companion Diagnostics, Workflow and Quality Control, Others), End User (Hospitals and Reference Laboratories, Diagnostic Laboratories, Pharmaceutical and Biotechnology Companies, Research and Academic Institutes, Others), and Geography (North America, Europe, Asia-Pacific, Rest of World).

By Offering

Dominant Subsegment: Software. The software category is expected to dominate the market.

Dominant: Software ~ 51%

The software segment accounted for 51% of the AI in Pathology market in 2025. Software is the leading offering because the value of AI in pathology resides in the algorithms and image-management platforms that detect cancer, grade tumors, quantify biomarkers, and orchestrate workflow, and because software generates recurring revenue through licenses, subscriptions, and cloud services. Cloud-native image management systems that unify slide viewing, collaboration, and integrated AI, such as enterprise platforms deployed across hospital networks, anchor the segment, while clinically validated algorithms address detection, grading, and biomarker scoring. FDA-cleared software and image-management stacks are normalizing multi-AI workflows, allowing laboratories to add modules over time and expanding software spend across the installed base. The shift toward foundation models trained on millions of slides deepens the software tier further by enabling broad, generalizable capabilities. Because algorithms improve continuously and scale without proportional hardware, software commands the largest and most durable share, while hardware such as scanners provides the imaging substrate and services support deployment, integration, and managed analytics.

By Technology

Dominant Subsegment: Machine Learning. The machine learning category is expected to dominate the market.

Dominant: Machine Learning ~ 45%

The machine learning segment accounted for 45% of the AI in Pathology market in 2025. Machine learning is the leading technology because it underpins the majority of deployed AI pathology applications, with convolutional and other neural networks trained on annotated whole-slide images powering cancer detection, grading, and biomarker quantification. Trained on large labeled datasets, machine-learning models deliver the pattern-recognition capabilities that pathologists rely on, and they form the foundation on which deep learning, a specialized subset, extends performance for complex histopathology. The segment's dominance reflects maturity, regulatory familiarity, and broad integration across cleared clinical tools from Tempus' Paige, Ibex, and others. Adjacent technologies are advancing quickly: computer vision powers image analysis and is among the fastest-growing approaches, while generative and foundation models trained on millions of slides are expanding rapidly for biomarker discovery and diagnostic co-pilots. While these newer approaches grow fast from smaller bases, machine learning retains leadership in 2025 through its breadth of validated, deployed clinical applications across the installed base.

By End User

Dominant Subsegment: Hospitals and Reference Laboratories. The hospitals and reference laboratories category is expected to dominate the market.

Dominant: Hospitals and Reference Laboratories ~ 47%

The hospitals and reference laboratories segment accounted for 47% of the AI in Pathology market in 2025. Hospitals and reference laboratories are the largest end user because they process the highest volume of pathology cases and have the scale, infrastructure, and clinical breadth to adopt digital pathology and enterprise AI platforms. These facilities anchor the installed base for whole-slide imaging and image-management systems, and they deploy AI to accelerate detection, standardize grading, and manage rising caseloads amid pathologist shortages. Large hospital networks and national laboratories are implementing enterprise platforms that unify slide management with integrated AI across many sites, exemplified by health systems and nationwide pathology networks adopting cloud-native image-management systems. This concentration of volume and infrastructure drives the bulk of AI pathology demand. At the same time, pharmaceutical and biotechnology companies and research and academic institutes are growing quickly as biomarker discovery and clinical-trial applications expand. Nonetheless, the volume, infrastructure, and clinical centrality of hospitals and reference laboratories secure their leadership across the forecast period.

AI in Pathology Market Region Analysis

Dominant Region: North America

North America accounted for 41% of the global AI in Pathology market revenue in 2025, representing the highest regional market share globally. The region's dominance reflects advanced healthcare infrastructure, high adoption of digital pathology, substantial AI investment, and the most active regulatory environment, particularly in the United States. North America hosts the largest concentration of AI pathology developers, including Tempus, Paige, PathAI, and Proscia, and benefits from a steady cadence of FDA authorizations, with AI pathology clearances rising to ten in 2025 and the FDA issuing clarifying guidance on AI-enabled devices. The region leads in foundation-model development, exemplified by the Tempus acquisition of Paige to build a large oncology foundation model, and in enterprise deployments across hospital and reference-laboratory networks. Strong precision-oncology and companion-diagnostic programs, deep venture and strategic investment, and integration with electronic health records reinforce adoption. A dense developer base, regulatory clarity, and digitized infrastructure anchor the region's continued leadership.

Dominant: North America ~ 41% (Largest)

Fastest Growing Region: Asia-Pacific

Asia-Pacific is the fastest-growing region in the AI in Pathology market. The region's elevated CAGR is driven by a large and rising cancer burden, an acute shortage of pathologists relative to population, expanding healthcare investment, and rapid digitization across China, Japan, India, South Korea, and Australia. Severe pathologist shortages in populous markets make AI augmentation and telepathology especially valuable for extending diagnostic capacity, and active regional developers in China, Korea, and Taiwan are scaling computational pathology platforms. Government digital-health initiatives, growing precision-oncology adoption, and increasing laboratory digitization are accelerating deployment, while lower-cost local solutions broaden access. The combination of high disease burden, workforce constraints, and rapid digitization positions Asia-Pacific as the principal source of incremental growth over the forecast period.

Regional Commentary

North America

North America accounted for 41% of the global AI in Pathology market revenue in 2025. The United States dominates on the strength of its developer base, high digital-pathology adoption, the most active FDA authorization and guidance environment, leadership in foundation models, and integration with precision-oncology and companion-diagnostic programs, while Canada contributes through hospital and academic adoption.

Europe

Europe is a large and advanced regional market, led by Germany, the United Kingdom, France, Italy, and Spain. Growth is supported by strong public health systems, regional digital-pathology initiatives, and the EU In Vitro Diagnostic Regulation, which raises the evidence bar and, through IVDR certification of leading AI tools, validates clinical performance. A strong base of European developers, including Aiforia, Visiopharm, Mindpeak, and Tribun Health, reinforces the region's position.

Asia-Pacific

Asia-Pacific is the fastest-growing region, propelled by a rising cancer burden, acute pathologist shortages, expanding healthcare investment, and rapid digitization across China, Japan, India, South Korea, and Australia. Regional developers in China, Korea, and Taiwan scale computational pathology platforms, while government digital-health programs and telepathology extend diagnostic access across large and underserved populations.

Rest of World

The Rest of World region, spanning Latin America, the Middle East, and Africa, is an emerging growth frontier. A rising cancer burden, severe shortages of pathologists, and limited laboratory capacity make AI augmentation and telepathology especially valuable, and government digitization initiatives and partnerships, such as large integrated healthcare networks adopting AI image-management systems, are expanding access across these markets.

AI in Pathology Market Competitive Landscape

The AI in Pathology market is classified as Moderately Concentrated. A group of leading AI pathology developers and diagnostics majors, including Tempus with Paige, Roche, Philips, PathAI, and Ibex, holds substantial share through advanced platforms, clinical collaborations, and regulatory clearances, while a dynamic field of specialized providers such as Proscia, Indica Labs, Aiforia, Visiopharm, Hologic, and Mindpeak competes across image management, biomarker analysis, and specific cancer indications, increasing competition in fast-growing segments.

The competitive landscape can be evaluated across the following dimensions:

Market concentration: Moderately concentrated, with leading platform developers and diagnostics majors alongside a fast-growing field of specialized challengers.
Leading players: Tempus (Paige), Roche, Philips, PathAI, and Ibex anchor the top tier through validated platforms and clearances.
Geographic reach: Leaders operate global commercial networks, with nationwide pathology networks and partnerships extending into Europe, Latin America, and Asia-Pacific.
Product portfolio strength: Top players hold integrated portfolios spanning image management, cleared detection and grading algorithms, and biomarker analytics.
Pipeline strength: Deep pipelines in multi-tissue detection, prognostic and predictive tools, and foundation models, including breakthrough-designated platforms.
Strategic partnerships: Extensive collaborations, such as Roche with PathAI and Ibex, and Leica Biosystems with Paige, embed AI into diagnostics and scanners.
M&A activity: Active consolidation, led by Tempus' acquisition of Paige to build a large oncology foundation model.
Regulatory strength: FDA authorizations and EU IVDR certifications are decisive competitive assets, with clearances rising to ten in 2025.
Innovation focus: Foundation models, generative AI co-pilots, multi-tissue detection, prognostic and predictive biomarkers, and cloud-native enterprise platforms.

AI in Pathology Market Recent Developmental Activities

In August 2025, Tempus AI, Inc. completed the acquisition of Paige, merging Paige's 7 million digitized slides with Tempus' multiomic data with the stated goal of building the largest foundation model in oncology. Strategic significance: Creates a leading data and foundation-model position and accelerates the path from discovery to regulated AI pathology tools.

In August 2025, PathAI, Inc. (with Moffitt Cancer Center) announced a multi-year strategic partnership to implement the AISight Dx cloud-native digital pathology platform across Moffitt's pathology operations. Strategic significance: Anchors enterprise-scale AI pathology adoption at a leading cancer center and showcases unified slide management with integrated AI.

AI in Pathology Market Segmentation

AI in Pathology Market by Offering

Software
Hardware
Services

AI in Pathology Market by Technology

Machine Learning
Deep Learning
Computer Vision
Generative and Foundation Models
Others

AI in Pathology Market by Application

Disease Diagnosis and Prognosis
Oncology Pathology
Non-Oncologic Pathology
Drug Discovery and Development
Companion Diagnostics
Workflow and Quality Control
Others

AI in Pathology Market by End User

Hospitals and Reference Laboratories
Diagnostic Laboratories
Pharmaceutical and Biotechnology Companies
Research and Academic Institutes
Others

AI in Pathology Market by Geography

North America AI in Pathology Market
United States AI in Pathology Market Size in USD million (2023-2034)
Canada AI in Pathology Market Size in USD million (2023-2034)
Mexico AI in Pathology Market Size in USD million (2023-2034)
Europe AI in Pathology Market
Germany AI in Pathology Market Size in USD million (2023-2034)
United Kingdom AI in Pathology Market Size in USD million (2023-2034)
France AI in Pathology Market Size in USD million (2023-2034)
Italy AI in Pathology Market Size in USD million (2023-2034)
Spain AI in Pathology Market Size in USD million (2023-2034)
Rest of Europe AI in Pathology Market Size in USD million (2023-2034)
Asia-Pacific AI in Pathology Market
China AI in Pathology Market Size in USD million (2023-2034)
Japan AI in Pathology Market Size in USD million (2023-2034)
India AI in Pathology Market Size in USD million (2023-2034)
Australia AI in Pathology Market Size in USD million (2023-2034)
South Korea AI in Pathology Market Size in USD million (2023-2034)
Rest of Asia-Pacific AI in Pathology Market Size in USD million (2023-2034)
Rest of the World (RoW) AI in Pathology Market
Middle East AI in Pathology Market Size in USD million (2023-2034)
Africa AI in Pathology Market Size in USD million (2023-2034)
South America AI in Pathology Market Size in USD million (2023-2034)

Key Takeaways from the AI in Pathology Market Report Study

Market size analysis for the current AI in pathology market size (2025), and market forecast for 9 years (2026 to 2034).
Top key product/technology developments, mergers, acquisitions, partnerships, and joint ventures that happened over the last 3 years.
Key companies dominating the global AI in pathology market.
Various opportunities available for competitors in the AI in pathology market space.
What are the top-performing segments in 2025? How will these segments perform in 2034?
Which are the top-performing regions and countries in the current AI in pathology market scenario?
Which are the regions and countries where companies should concentrate their opportunities for AI in pathology market growth in the future?

Target audience who can benefit from this AI in pathology market report study

AI in Pathology product providers
Research organizations and consulting companies
AI in Pathology-related organizations, associations, forums, and other alliances
Government and corporate offices
Start-up companies, venture capitalists, and private equity firms
Distributors and traders dealing in AI in pathology

Various end-users who want to know more about the AI in pathology market and the latest technological developments in the AI in pathology market.

Frequently Asked Questions:

Q1. What is the growth rate of the AI in Pathology market?

The AI in Pathology market is projected to expand at a CAGR of 24.7% during the forecast period from 2026-2034.

Q2. What is the market size of the AI in Pathology market?

The AI in Pathology market is estimated at USD 0.13 billion in 2025 and is projected to reach USD 0.95 billion by 2034.

Q3. Which region dominates the AI in Pathology market?

North America dominated the AI in Pathology market with a 41% share of global revenue in 2025, supported by advanced healthcare infrastructure, high digital-pathology adoption, the most active FDA authorization and guidance environment, leadership in foundation models, and a dense base of AI pathology developers. Asia-Pacific is the fastest-growing region over the forecast period.

Q4. What are the key drivers of the AI in Pathology market?

The principal drivers are the rising global cancer burden, with the International Agency for Research on Cancer projecting cancer cases to rise from 20 million in 2022 to 35 million by 2050; a worsening shortage of pathologists amid rising caseloads; accelerating regulatory clearances, with FDA authorizations rising to ten in 2025; the transition from glass slides to digital pathology; and the emergence of foundation models and generative AI co-pilots.

Q5. Who are the major players in the AI in Pathology market?

The major players include Tempus AI, Inc. (Paige), F. Hoffmann-La Roche Ltd, Koninklijke Philips N.V., PathAI, Inc., Ibex Medical Analytics Ltd., Proscia Inc., Indica Labs, Inc., Aiforia Technologies Plc, Hologic, Inc., and Visiopharm A/S, among other active developers profiled in the Competitive Landscape section, along with Akoya Biosciences, Mindpeak, and ArteraAI. Tempus with Paige, Roche, Philips, PathAI, and Ibex lead through validated platforms and regulatory clearances.

1. AI in Pathology Market Report Introduction

1.1 Scope of the Study
1.2 Market Segmentation
1.3 Market Assumptions

2. AI in Pathology Market Executive Summary

2.1 Market at a Glance

3. AI in Pathology Market Key Factors Analysis

3.1 AI in Pathology Market Drivers
- 3.1.1 Rising Global Cancer Burden and Slide Volumes
- 3.1.2 Worsening Shortage of Pathologists
- 3.1.3 Accelerating Regulatory Clearances
- 3.1.4 Transition to Digital Pathology and Foundation Models
3.2 AI in Pathology Market Restraints and Challenges
- 3.2.1 High Capital and Infrastructure Requirements
- 3.2.2 Regulatory, Validation, and Trust Barriers
- 3.2.3 Interoperability, Workforce, and Reimbursement Gaps
3.3 AI in Pathology Market Opportunities
- 3.3.1 Foundation Models and Generative AI Co-Pilots
- 3.3.2 Emerging-Market and Telepathology Expansion

4. Impact Analysis: AI, Geopolitical, Trade, and Economic Developments

5. Regulatory Analysis

5.1 United States
5.2 Europe
5.3 Japan
5.4 China

6. AI in Pathology Market Porter's Five Forces Analysis

6.1 Bargaining Power of Suppliers
6.2 Bargaining Power of Buyers
6.3 Threat of New Entrants
6.4 Threat of Substitutes
6.5 Competitive Rivalry

7. AI in Pathology Market Assessment

7.1 By Offering
- 7.1.1 Software
- 7.1.2 Hardware
- 7.1.3 Services
7.2 By Technology
- 7.2.1 Machine Learning
- 7.2.2 Deep Learning
- 7.2.3 Computer Vision
- 7.2.4 Generative and Foundation Models
- 7.2.5 Others
7.3 By Application
- 7.3.1 Disease Diagnosis and Prognosis
  - 7.3.1.1 Oncology Pathology
  - 7.3.1.2 Non-Oncologic Pathology
- 7.3.2 Drug Discovery and Development
- 7.3.3 Companion Diagnostics
- 7.3.4 Workflow and Quality Control
- 7.3.5 Others
7.4 By End User
- 7.4.1 Hospitals and Reference Laboratories
- 7.4.2 Diagnostic Laboratories
- 7.4.3 Pharmaceutical and Biotechnology Companies
- 7.4.4 Research and Academic Institutes
- 7.4.5 Others
7.5 By Geography
- 7.5.1 North America
  - 7.5.1.1 United States AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.1.2 Canada AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.1.3 Mexico AI in Pathology Market Size in USD million (2023-2034)
- 7.5.2 Europe
  - 7.5.2.1 Germany AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.2.2 United Kingdom AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.2.3 France AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.2.4 Italy AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.2.5 Spain AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.2.6 Rest of Europe AI in Pathology Market Size in USD million (2023-2034)
- 7.5.3 Asia-Pacific
  - 7.5.3.1 China AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.3.2 Japan AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.3.3 India AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.3.4 Australia AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.3.5 South Korea AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.3.6 Rest of Asia-Pacific AI in Pathology Market Size in USD million (2023-2034)
- 7.5.4 Rest of World
  - 7.5.4.1 Middle East AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.4.2 Africa AI in Pathology Market Size in USD million (2023-2034)
  - 7.5.4.3 South America AI in Pathology Market Size in USD million (2023-2034)

8. AI in Pathology Market Competitive Landscape

8.1 Market Concentration and Structure
8.2 Competitive Positioning and Market Share Analysis (Premium Offering)

9. AI in Pathology Market Startup Funding and Investment Trends

10. AI in Pathology Market Company and Product Profiles

10.1 Tempus AI, Inc. (Paige)
- 10.1.1 Company Overview
- 10.1.2 Company Snapshot
- 10.1.3 Financial Overview
- 10.1.4 Product Portfolio
- 10.1.5 Strategic Initiatives / Entropy
10.2 F. Hoffmann-La Roche Ltd
- 10.2.1 Company Overview
- 10.2.2 Company Snapshot
- 10.2.3 Financial Overview
- 10.2.4 Product Portfolio
- 10.2.5 Strategic Initiatives / Entropy
10.3 Koninklijke Philips N.V.
- 10.3.1 Company Overview
- 10.3.2 Company Snapshot
- 10.3.3 Financial Overview
- 10.3.4 Product Portfolio
- 10.3.5 Strategic Initiatives / Entropy
10.4 PathAI, Inc.
- 10.4.1 Company Overview
- 10.4.2 Company Snapshot
- 10.4.3 Financial Overview
- 10.4.4 Product Portfolio
- 10.4.5 Strategic Initiatives / Entropy
10.5 Ibex Medical Analytics Ltd.
- 10.5.1 Company Overview
- 10.5.2 Company Snapshot
- 10.5.3 Financial Overview
- 10.5.4 Product Portfolio
- 10.5.5 Strategic Initiatives / Entropy
10.6 Proscia Inc.
- 10.6.1 Company Overview
- 10.6.2 Company Snapshot
- 10.6.3 Financial Overview
- 10.6.4 Product Portfolio
- 10.6.5 Strategic Initiatives / Entropy
10.7 Indica Labs, Inc.
- 10.7.1 Company Overview
- 10.7.2 Company Snapshot
- 10.7.3 Financial Overview
- 10.7.4 Product Portfolio
- 10.7.5 Strategic Initiatives / Entropy
10.8 Aiforia Technologies Plc
- 10.8.1 Company Overview
- 10.8.2 Company Snapshot
- 10.8.3 Financial Overview
- 10.8.4 Product Portfolio
- 10.8.5 Strategic Initiatives / Entropy
10.9 Hologic, Inc.
- 10.9.1 Company Overview
- 10.9.2 Company Snapshot
- 10.9.3 Financial Overview
- 10.9.4 Product Portfolio
- 10.9.5 Strategic Initiatives / Entropy
10.10 Visiopharm A/S
- 10.10.1 Company Overview
- 10.10.2 Company Snapshot
- 10.10.3 Financial Overview
- 10.10.4 Product Portfolio
- 10.10.5 Strategic Initiatives / Entropy

For illustrative purposes, only the top 10 companies are listed in the Table of Contents. The report may include analysis and references to additional companies where relevant to the market assessment.