AI in Pathology Market by Component (Hardware, Software), Neural Network (Convolutional neural networks (CNNs), Generative adversarial networks (GANs), Recurrent neural networks (RNNs)), Application, End-User - Global Forecast 2024-2030

AI in Pathology Market by Component (Hardware, Software), Neural Network (Convolutional neural networks (CNNs), Generative adversarial networks (GANs), Recurrent neural networks (RNNs)), Application, End-User - Global Forecast 2024-2030


The AI in Pathology Market size was estimated at USD 29.01 million in 2023 and expected to reach USD 33.36 million in 2024, at a CAGR 15.33% to reach USD 78.75 million by 2030.

Artificial intelligence (AI) in pathology integrates advanced computational techniques, machine learning algorithms, and image analysis tools to improve pathological diagnoses' speed, accuracy, and efficiency by automating various aspects of the diagnostic process. Increasing demand for accurate and quick diagnostics, the rising chronic diseases prevalence such as cancer that require timely diagnosis, and continuous developments in digital pathology infrastructure strongly contribute to the growth of the market. In addition, ongoing investments in research and development activities and supportive government initiatives aimed at promoting healthcare digitization. Furthermore, the development and integration of AI-based solutions in pathology can be an expensive affair for many healthcare organizations. Also, the usage of cloud-based solutions for sharing patient data raises concerns about data breaches and unauthorized access to sensitive information. Apart from this, rapid advancements in machine learning techniques & artificial intelligence capabilities create a potential opportunity for market growth. Additionally, emerging technologies such as blockchain can be leveraged to ensure secure storage and transfer of patient data.

Regional Insights

In the Americas, significant investments have been made in AI-driven pathology solutions to advance digital diagnostics. The Food and Drug Administration has also started approving AI-based medical devices, demonstrating an increasing acceptance of such technologies. The European Commission's program has provided significant funding for projects focusing on digital transformation in health and care. Improved healthcare infrastructure in the EU region presents a unique opportunity for AI-based pathology solutions. In the APAC region, major players have made significant investments in digital diagnostics. Government initiatives have also supported R&D in this sector, leading to numerous patents and research publications. Also, the development of healthcare infrastructure in the developing economies of the APAC region endorses the adoption of digital healthcare solutions.

Market Insights

Market Dynamics

The market dynamics represent an ever-changing landscape of the AI in Pathology Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

Market Drivers
  • Increasing digitalization of pathology worldwide
  • Growing need for telepathology with the prevalence of chronic disease
Market Restraints
  • High cost associated with AI in pathology
Market Opportunities
  • Technological advancements in AI in pathology
  • Rising demand for personalized and customized medicine
Market Challenges
  • Concerns associated with data privacy
Market Segmentation Analysis
  • Component: Extensive software applications in pathology for seamless workflows and efficient data management
  • Neural Network: Increasing generative adversarial networks adoption due to diagnostic accuracy and efficiency
  • Application: Wide utilization of AI in pathology for disease diagnosis to facilitate early detection of diseases
  • End-User: Expansion of pathology AI in pharmaceuticals & biotechnology companies for discovering potential therapeutics
Market Disruption Analysis
  • Porter’s Five Forces Analysis
  • Value Chain & Critical Path Analysis
  • Pricing Analysis
  • Technology Analysis
  • Patent Analysis
  • Trade Analysis
  • Regulatory Framework Analysis
FPNV Positioning Matrix

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the AI in Pathology Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the AI in Pathology Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments

Microsoft Collab to Build World’s Largest Pathology, Oncology Imaging AI

Microsoft and healthcare technology company Paige have partnered to create image-based AI models for digital pathology and oncology, with the goal of revolutionizing cancer diagnosis and patient care. Paige has developed an AI model that has been trained on over 1 billion images from half a million pathology slides across various cancer types. This collaboration aims to expand the model to an even larger scale by incorporating up to 4 million digitized microscopy slides.

PathAI Announces PathExplore, an AI-powered Pathology Panel to Unlock Untapped Insights from the Tumor Microenvironment

PathExplore, powered by artificial intelligence, is a groundbreaking technology that provides single-cell resolution of the tumor microenvironment from H&E whole-slide images. This innovative technology aims to unlock valuable insights into disease states, potentially leading to improved patient outcomes and more targeted oncology therapies. Unlike current technologies, PathExplore offers a unique combination of deep resolution and scalability, making it suitable for analyzing massive numbers of patient samples.

Paige and Leica Biosystems Announce Expanded Partnership to Enhance Use of Image Management and Artificial Intelligence Technology in Global Digital Pathology Workflows

Paige and Leica Biosystems have announced an expanded partnership to enhance the utilization of digital pathology workflows. As part of this collaboration, a co-branded version of Paige's Platform was introduced, serving as the central interface connecting pathologists with Leica Biosystems hardware. This partnership provides users of Aperio GT 450 scanners with comprehensive access to Paige's suite of digital pathology software, encompassing the FullFocus viewer, the AI-powered worklist FullFolio, and a range of other AI software solutions.

Strategy Analysis & Recommendation

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the AI in Pathology Market. This critical assessment involves a thorough analysis of the organization’s resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

Key Company Profiles

The report delves into recent significant developments in the AI in Pathology Market, highlighting leading vendors and their innovative profiles. These include aetherAI, Aiforia Technologies Oyj, Akoya Biosciences, Inc., Deep Bio, Inc., Evident Corporation, F. Hoffmann-La Roche Ltd., Ibex Medical Analytics Ltd., Indica Labs, Inc., Inspirata, Inc., LUMEA, Inc., MindPeak GmbH, Nucleai Inc., OptraSCAN Inc., Paige.AI, Inc., PathAI, Inc., Proscia Inc., Techcyte, Inc., Tempus Labs, Inc., Tribun Health, Visikol, Inc. by CELLINK, and Visiopharm A/S.

Market Segmentation & Coverage

This research report categorizes the AI in Pathology Market to forecast the revenues and analyze trends in each of the following sub-markets:
  • Component
  • Hardware
  • Software
  • Neural Network
  • Convolutional neural networks (CNNs)
  • Generative adversarial networks (GANs)
  • Recurrent neural networks (RNNs)
  • Application
  • Clinical Workflow
  • Disease Diagnosis & Prognosis
  • Drug Discovery
  • Training & Education
  • End-User
  • Academic & Research Institutes
  • Hospitals
  • Pharmaceuticals & Biotechnology Companies
  • Region
  • Americas
  • Argentina
  • Brazil
  • Canada
  • Mexico
  • United States
  • California
  • Florida
  • Illinois
  • New York
  • Ohio
  • Pennsylvania
  • Texas
  • Asia-Pacific
  • Australia
  • China
  • India
  • Indonesia
  • Japan
  • Malaysia
  • Philippines
  • Singapore
  • South Korea
  • Taiwan
  • Thailand
  • Vietnam
  • Europe, Middle East & Africa
  • Denmark
  • Egypt
  • Finland
  • France
  • Germany
  • Israel
  • Italy
  • Netherlands
  • Nigeria
  • Norway
  • Poland
  • Qatar
  • Russia
  • Saudi Arabia
  • South Africa
  • Spain
  • Sweden
  • Switzerland
  • Turkey
  • United Arab Emirates
  • United Kingdom


Please Note: PDF & Excel + Online Access - 1 Year


1. Preface
1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders
2. Research Methodology
2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update
3. Executive Summary
4. Market Overview
5. Market Insights
5.1. Market Dynamics
5.1.1. Drivers
5.1.1.1. Increasing digitalization of pathology worldwide
5.1.1.2. Growing need for telepathology with the prevalence of chronic disease
5.1.2. Restraints
5.1.2.1. High cost associated with AI in pathology
5.1.3. Opportunities
5.1.3.1. Technological advancements in AI in pathology
5.1.3.2. Rising demand for personalized and customized medicine
5.1.4. Challenges
5.1.4.1. Concerns associated with data privacy
5.2. Market Segmentation Analysis
5.2.1. Component: Extensive software applications in pathology for seamless workflows and efficient data management
5.2.2. Neural Network: Increasing generative adversarial networks adoption due to diagnostic accuracy and efficiency
5.2.3. Application: Wide utilization of AI in pathology for disease diagnosis to facilitate early detection of diseases
5.2.4. End-User: Expansion of pathology AI in pharmaceuticals & biotechnology companies for discovering potential therapeutics
5.3. Market Disruption Analysis
5.4. Porter’s Five Forces Analysis
5.4.1. Threat of New Entrants
5.4.2. Threat of Substitutes
5.4.3. Bargaining Power of Customers
5.4.4. Bargaining Power of Suppliers
5.4.5. Industry Rivalry
5.5. Value Chain & Critical Path Analysis
5.6. Pricing Analysis
5.7. Technology Analysis
5.8. Patent Analysis
5.9. Trade Analysis
5.10. Regulatory Framework Analysis
6. AI in Pathology Market, by Component
6.1. Introduction
6.2. Hardware
6.3. Software
7. AI in Pathology Market, by Neural Network
7.1. Introduction
7.2. Convolutional neural networks (CNNs)
7.3. Generative adversarial networks (GANs)
7.4. Recurrent neural networks (RNNs)
8. AI in Pathology Market, by Application
8.1. Introduction
8.2. Clinical Workflow
8.3. Disease Diagnosis & Prognosis
8.4. Drug Discovery
8.5. Training & Education
9. AI in Pathology Market, by End-User
9.1. Introduction
9.2. Academic & Research Institutes
9.3. Hospitals
9.4. Pharmaceuticals & Biotechnology Companies
10. Americas AI in Pathology Market
10.1. Introduction
10.2. Argentina
10.3. Brazil
10.4. Canada
10.5. Mexico
10.6. United States
11. Asia-Pacific AI in Pathology Market
11.1. Introduction
11.2. Australia
11.3. China
11.4. India
11.5. Indonesia
11.6. Japan
11.7. Malaysia
11.8. Philippines
11.9. Singapore
11.10. South Korea
11.11. Taiwan
11.12. Thailand
11.13. Vietnam
12. Europe, Middle East & Africa AI in Pathology Market
12.1. Introduction
12.2. Denmark
12.3. Egypt
12.4. Finland
12.5. France
12.6. Germany
12.7. Israel
12.8. Italy
12.9. Netherlands
12.10. Nigeria
12.11. Norway
12.12. Poland
12.13. Qatar
12.14. Russia
12.15. Saudi Arabia
12.16. South Africa
12.17. Spain
12.18. Sweden
12.19. Switzerland
12.20. Turkey
12.21. United Arab Emirates
12.22. United Kingdom
13. Competitive Landscape
13.1. Market Share Analysis, 2023
13.2. FPNV Positioning Matrix, 2023
13.3. Competitive Scenario Analysis
13.3.1. Microsoft Collab to Build World’s Largest Pathology, Oncology Imaging AI
13.3.2. PathAI Announces PathExplore, an AI-powered Pathology Panel to Unlock Untapped Insights from the Tumor Microenvironment
13.3.3. Paige and Leica Biosystems Announce Expanded Partnership to Enhance Use of Image Management and Artificial Intelligence Technology in Global Digital Pathology Workflows
13.4. Strategy Analysis & Recommendation
14. Competitive Portfolio
14.1. Key Company Profiles
14.2. Key Product Portfolio

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