Al In Pathology Market
Al in Pathology Market Forecasts to 2030 - Global Analysis By Offering (Software, Hardware and Services), Workflow, Deployment Mode, Technology, Application, End User and By Geography
|
Years Covered |
2022-2030 |
|
Estimated Year Value (2024) |
US $82.8 MN |
|
Projected Year Value (2030) |
US $205.9 MN |
|
CAGR (2024 - 2030) |
16.4% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
North America |
|
Highest Growing Market |
Asia Pacific |
According to Stratistics MRC, the Global Al in Pathology Market is accounted for $82.8 million in 2024 and is expected to reach $205.9 million by 2030 growing at a CAGR of 16.4% during the forecast period. AI in pathology is the use of artificial intelligence techniques, such as machine learning and deep learning, to analyze digital pathology images. These images are created by scanning traditional glass slides, allowing for computer-aided diagnosis, disease prediction, and treatment planning. AI algorithms can assist pathologists in identifying patterns, quantifying features, and detecting abnormalities in tissue samples, ultimately improving accuracy and efficiency in pathology workflows.
According to the US Department of Health and Human Services, since the pandemic, Medicare beneficiaries have increased their use of telemedicine in the United States. In-person healthcare visits in the US were registered at 1.1 billion in 2019 and 989 million in 2020.
Market Dynamics:
Driver:
Increasing demand for personalized medicine
The growing demand for personalized medicine in pathology is driving the integration of AI technologies. AI enables precise diagnostics, tailored treatments, and predictive analytics based on individual genetic profiles. This trend enhances patient outcomes by identifying the most effective therapies and minimizing adverse effects. As precision medicine advances, AI's role in pathology becomes crucial in improving accuracy, efficiency, and overall healthcare delivery, fueling market growth.
Restraint:
Inadequate interoperability issues with legacy systems
Inadequate interoperability with legacy systems in AI pathology can hinder seamless data integration, reducing the effectiveness of advanced AI tools. This incompatibility leads to delays, errors in diagnosis, and fragmented patient records, impairing workflow efficiency. The inability to exchange data across platforms also limits AI's full potential in enhancing personalized treatments and collaboration. As a result, the market faces challenges in fully adopting AI technologies, impacting overall healthcare delivery.
Opportunity:
Growing digitalization of pathology
The digitalization of pathology is transforming the market by enabling faster, more accurate diagnoses. AI-powered tools streamline image analysis, automate workflows, and enhance data management, improving efficiency and precision. Digital pathology platforms facilitate remote consultations, allowing pathologists to collaborate globally. This digital shift is driving innovation in diagnostics, accelerating research, and supporting personalized treatment plans, leading to rapid growth in the market.
Threat:
High cost of digital pathology systems
The high cost of digital pathology systems with the market creates barriers to adoption, particularly for smaller healthcare facilities. These expenses can lead to budget constraints, limiting access to advanced diagnostic tools and technology. As a result, it may contribute to unequal healthcare delivery, slow down innovation, and hinder the widespread use of AI in pathology, potentially delaying improvements in patient care and diagnostic accuracy.
Covid-19 Impact:
COVID-19 accelerated the adoption of AI in pathology as healthcare systems sought efficient ways to handle increased workload and ensure safety. AI-driven tools helped speed up diagnostics, reduce human contact, and manage resources more effectively. However, the pandemic also highlighted challenges such as limited infrastructure, data privacy concerns, and budget constraints. Despite these, the crisis spurred greater interest and investment in AI technologies for pathology, shaping future growth.
The computer vision segment is expected to be the largest market share during the forecast period
The computer vision segment is expected to account for the largest market share during the forecast period. It automates tasks like detecting abnormalities, classifying diseases, and quantifying tissue changes, improving efficiency and reducing human error. With deep learning algorithms, computer vision accelerates the diagnostic process and supports pathologists in making more precise, consistent decisions. Its integration is transforming pathology by enabling faster, more accurate disease detection and treatment planning.
The disease diagnosis segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the disease diagnosis segment is predicted to witness the highest growth rate. AI systems assist pathologists in identifying abnormalities, detecting diseases early, and predicting patient outcomes with high accuracy. By automating image analysis and pattern recognition, AI enhances diagnostic efficiency, reduces human error, and supports personalized treatment plans. This technology is particularly valuable in areas like cancer detection, enabling faster and more reliable diagnoses.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share due to advanced healthcare infrastructure, increasing demand for precision medicine, and rising adoption of digital pathology. AI technologies are enhancing diagnostic accuracy, particularly in cancer detection and disease management. With strong investments from both public and private sectors, leads in research, development, and integration of AI-driven solutions, shaping the future of pathology through improved efficiency and patient care.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by advancements in healthcare technology and increasing demand for precision medicine. Economic growth in many Asia Pacific countries is leading to increased investments in healthcare technology and infrastructure, facilitating the integration of AI in pathology. Additionally, the increasing need for personalized treatment plans is propelling the adoption of AI in pathology.
Key players in the market
Some of the key players in Al in Pathology market include Siemens Healthineers, Canon Medical Systems, Proscia, Zebra Medical Vision, IBM Watson Health, Philips Healthcare, Visiopharm, Tempus Labs, DeepMind, Medtronic, Konica Minolta, Eizo Corporation, Becton Dickinson (BD), Pathologix and Densitas.
Key Developments:
In November 2024, Siriraj Piyamaharajkarun Hospital (SiPH) announced a successful transformation of its Pathology Information System (PIS) using advanced computational technologies and artificial intelligence. In collaboration with IBM, the system now integrates laboratory workflows, image scanning systems, and centralized data processing, establishing a cohesive approach for pathological cancer diagnosis and laying the foundation for SiPH’s future advancements in cancer diagnostics..
In April 2024, Practice technology leader and EHR pioneer ModMed® announced that it will collaborate with Medtronic, the world’s largest medtech company, to enhance the documentation of polyp detection by utilizing the AI capabilities of the GI Genius system sold by Medtronic.
Offerings Covered:
• Software
• Hardware
• Services
Workflows Covered:
• Pre-Analytical
• Analytical
• Post-Analytical
Deployment Modes Covered:
• Cloud-Based
• On-Premise
Technologies Covered:
• Machine Learning (ML)
• Deep Learning (DL)
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning (RL)
• Other Technologies
Applications Covered:
• Digital Pathology
• Disease Diagnosis
• Drug Discovery
• Personalized Medicine
• Other Applications
End Users Covered:
• Hospitals & Diagnostic Laboratories
• Pharmaceutical and Biotechnology Companies
• Research Institutions
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 End User Analysis
3.9 Emerging Markets
3.10 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Al in Pathology Market, By Offering
5.1 Introduction
5.2 Software
5.2.1 AI-Based Diagnostic Software
5.2.2 Digital Pathology Solutions
5.2.3 Image Analysis Software
5.3 Hardware
5.3.1 Digital Slide Scanners
5.3.2 Imaging Devices
5.3.3 Workstations and Touch Devices
5.4 Services
5.4.1 Consulting Services
5.4.2 Training and Education
5.4.3 Software Maintenance and Support
6 Global Al in Pathology Market, By Workflow
6.1 Introduction
6.2 Pre-Analytical
6.3 Analytical
6.4 Post-Analytical
7 Global Al in Pathology Market, By Deployment Mode
7.1 Introduction
7.2 Cloud-Based
7.3 On-Premise
8 Global Al in Pathology Market, By Technology
8.1 Introduction
8.2 Machine Learning (ML)
8.3 Deep Learning (DL)
8.4 Natural Language Processing (NLP)
8.5 Computer Vision
8.6 Reinforcement Learning (RL)
8.7 Other Technologies
9 Global Al in Pathology Market, By Application
9.1 Introduction
9.2 Digital Pathology
9.3 Disease Diagnosis
9.4 Drug Discovery
9.5 Personalized Medicine
9.6 Other Applications
10 Global Al in Pathology Market, By End User
10.1 Introduction
10.2 Hospitals & Diagnostic Laboratories
10.3 Pharmaceutical and Biotechnology Companies
10.4 Research Institutions
10.5 Other End Users
11 Global Al in Pathology Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 Europe
11.3.1 Germany
11.3.2 UK
11.3.3 Italy
11.3.4 France
11.3.5 Spain
11.3.6 Rest of Europe
11.4 Asia Pacific
11.4.1 Japan
11.4.2 China
11.4.3 India
11.4.4 Australia
11.4.5 New Zealand
11.4.6 South Korea
11.4.7 Rest of Asia Pacific
11.5 South America
11.5.1 Argentina
11.5.2 Brazil
11.5.3 Chile
11.5.4 Rest of South America
11.6 Middle East & Africa
11.6.1 Saudi Arabia
11.6.2 UAE
11.6.3 Qatar
11.6.4 South Africa
11.6.5 Rest of Middle East & Africa
12 Key Developments
12.1 Agreements, Partnerships, Collaborations and Joint Ventures
12.2 Acquisitions & Mergers
12.3 New Product Launch
12.4 Expansions
12.5 Other Key Strategies
13 Company Profiling
13.1 Siemens Healthineers
13.2 Canon Medical Systems
13.3 Proscia
13.4 Zebra Medical Vision
13.5 IBM Watson Health
13.6 Philips Healthcare
13.7 Visiopharm
13.8 Tempus Labs
13.9 DeepMind
13.10 Medtronic
13.13 Konica Minolta
13.12 Eizo Corporation
13.13 Becton Dickinson (BD)
13.14 Pathologix
13.15 Densitas
List of Tables
1 Global Al in Pathology Market Outlook, By Region (2022-2030) ($MN)
2 Global Al in Pathology Market Outlook, By Offering (2022-2030) ($MN)
3 Global Al in Pathology Market Outlook, By Software (2022-2030) ($MN)
4 Global Al in Pathology Market Outlook, By AI-Based Diagnostic Software (2022-2030) ($MN)
5 Global Al in Pathology Market Outlook, By Digital Pathology Solutions (2022-2030) ($MN)
6 Global Al in Pathology Market Outlook, By Image Analysis Software (2022-2030) ($MN)
7 Global Al in Pathology Market Outlook, By Hardware (2022-2030) ($MN)
8 Global Al in Pathology Market Outlook, By Digital Slide Scanners (2022-2030) ($MN)
9 Global Al in Pathology Market Outlook, By Imaging Devices (2022-2030) ($MN)
10 Global Al in Pathology Market Outlook, By Workstations and Touch Devices (2022-2030) ($MN)
11 Global Al in Pathology Market Outlook, By Services (2022-2030) ($MN)
12 Global Al in Pathology Market Outlook, By Consulting Services (2022-2030) ($MN)
13 Global Al in Pathology Market Outlook, By Training and Education (2022-2030) ($MN)
14 Global Al in Pathology Market Outlook, By Software Maintenance and Support (2022-2030) ($MN)
15 Global Al in Pathology Market Outlook, By Workflow (2022-2030) ($MN)
16 Global Al in Pathology Market Outlook, By Pre-Analytical (2022-2030) ($MN)
17 Global Al in Pathology Market Outlook, By Analytical (2022-2030) ($MN)
18 Global Al in Pathology Market Outlook, By Post-Analytical (2022-2030) ($MN)
19 Global Al in Pathology Market Outlook, By Deployment Mode (2022-2030) ($MN)
20 Global Al in Pathology Market Outlook, By Cloud-Based (2022-2030) ($MN)
21 Global Al in Pathology Market Outlook, By On-Premise (2022-2030) ($MN)
22 Global Al in Pathology Market Outlook, By Technology (2022-2030) ($MN)
23 Global Al in Pathology Market Outlook, By Machine Learning (ML) (2022-2030) ($MN)
24 Global Al in Pathology Market Outlook, By Deep Learning (DL) (2022-2030) ($MN)
25 Global Al in Pathology Market Outlook, By Natural Language Processing (NLP) (2022-2030) ($MN)
26 Global Al in Pathology Market Outlook, By Computer Vision (2022-2030) ($MN)
27 Global Al in Pathology Market Outlook, By Reinforcement Learning (RL) (2022-2030) ($MN)
28 Global Al in Pathology Market Outlook, By Other Technologies (2022-2030) ($MN)
29 Global Al in Pathology Market Outlook, By Application (2022-2030) ($MN)
30 Global Al in Pathology Market Outlook, By Digital Pathology (2022-2030) ($MN)
31 Global Al in Pathology Market Outlook, By Disease Diagnosis (2022-2030) ($MN)
32 Global Al in Pathology Market Outlook, By Drug Discovery (2022-2030) ($MN)
33 Global Al in Pathology Market Outlook, By Personalized Medicine (2022-2030) ($MN)
34 Global Al in Pathology Market Outlook, By Other Applications (2022-2030) ($MN)
35 Global Al in Pathology Market Outlook, By End User (2022-2030) ($MN)
36 Global Al in Pathology Market Outlook, By Hospitals & Diagnostic Laboratories (2022-2030) ($MN)
37 Global Al in Pathology Market Outlook, By Pharmaceutical and Biotechnology Companies (2022-2030) ($MN)
38 Global Al in Pathology Market Outlook, By Research Institutions (2022-2030) ($MN)
39 Global Al in Pathology Market Outlook, By Other End Users (2022-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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