Product Code: GVR-4-68038-871-8
Artificial Intelligence In Diagnostics Market Summary
The global artificial intelligence in diagnostics market size was estimated at USD 1.97 billion in 2025 and is projected to reach USD 9.68 billion by 2033, growing at a CAGR of 21.74% from 2026 to 2033. Market growth is driven by advancements in machine learning and deep learning, enabling faster, more accurate diagnostic solutions.
In oncology, cardiology, and neurology, among the areas, the growing demand for early disease detection has led to increased adoption of AI technologies. For instance, in February 2024, Royal Philips introduced the Philips CT 5300, an advanced AI-powered CT system designed for diagnostics, interventional procedures, and screenings. The adaptable X-ray CT system enhances diagnostic accuracy, streamlines workflows, and optimizes system availability.
Rising prevalence of chronic diseases such as diabetes, cancer, cardiovascular disorders, etc., coupled with the increasing demand for early & accurate diagnosis, are significant factors driving market growth. The increasing incidence of cancer globally has led to a growing dependence on AI in the field of oncology. According to the NIH estimates of 2023, approximately 2.0 million individuals in the U.S. are diagnosed with cancer. Breast cancer was the most diagnosed cancer, with an estimated 297,790 cases in women and 2,800 cases in men. Similarly, according to the Centers for Disease Control and Prevention (CDC), 919,032 people died from cardiovascular disease in the U.S. in 2023, equivalent to one in every three deaths.
Such a high prevalence increases the diagnostic workload. Advancements in healthcare IT infrastructure and ongoing technological developments in cloud storage, computing, and machine learning algorithms support the integration of AI-powered systems into diagnostics to provide efficient & accurate diagnoses, allowing care providers to devise timely & appropriate treatment plans. Pathology and radiology services are witnessing a widespread adoption of AI-based algorithms. For instance, in January 2026, Alpenglow Biosciences and PathNet formed a strategic partnership to develop and commercialize 3D AI diagnostic tests for prostate and bladder cancer. The collaboration advances urologic oncology from 2D to 3D pathology in the U.S., integrating imaging, AI analytics, and workflows for enhanced accuracy.
"PathNet's leadership in urologic oncology, digitization, AI, and strong national footprint make them an exceptional partner as we bring clinical 3D pathology to market. Together, we are building diagnostic tools that deliver insights not achievable with conventional 2D histology."
Dr. Nicholas Reder, CEO of Alpenglow Biosciences
In addition, several AI-powered tools are used to diagnose chronic kidney disease (CKD) & kidney function tests, and various chronic diseases. For instance, in May 2024, Premier, Inc. partnered with AstraZeneca to launch the Uncover CKD - Care Collective initiative. The aim is to identify patients with undiagnosed CKD, raise awareness among healthcare providers, and assist U.S. health systems in improving their CKD diagnosis, treatment, and management. Leveraging Premier's PINC AI technology and services platform, the initiative seeks to address the increasing prevalence of undiagnosed CKD and its associated economic burden on the U.S. healthcare system.
Global Artificial Intelligence In Diagnostics Market Report Segmentation
This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends across sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global artificial intelligence in diagnostics market report based on component, diagnosis type, and region:
- Component Outlook (Revenue, USD Million, 2021 - 2033)
- Software
- Hardware
- Services
- Diagnosis Type Outlook (Revenue, USD Million, 2021 - 2033)
- Cardiology
- Oncology
- Pathology
- Radiology
- Chest and Lung
- Neurology
- Others
- Regional Outlook (Revenue, USD Million, 2021 - 2033)
- North America
- Europe
- UK
- Germany
- France
- Italy
- Spain
- Norway
- Denmark
- Sweden
- Asia Pacific
- Japan
- China
- India
- Australia
- South Korea
- Thailand
- Latin America
- Middle East and Africa (MEA)
- South Africa
- Saudi Arabia
- UAE
- Kuwait
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.1.1. Component
- 1.1.2. Diagnosis type
- 1.1.3. Regional scope
- 1.1.4. Estimates and forecast timeline.
- 1.2. Research Methodology
- 1.3. Information Procurement
- 1.3.1. Purchased database.
- 1.3.2. GVR's internal database
- 1.3.3. Secondary sources
- 1.3.4. Primary research
- 1.3.5. Details of primary research
- 1.4. Information or Data Analysis
- 1.4.1. Data analysis models
- 1.5. Market Formulation & Validation
- 1.6. Model Details
- 1.6.1. Commodity flow analysis (Model 1)
- 1.7. List of Secondary Sources
- 1.8. List of Primary Sources
- 1.9. Objectives
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.2.1. Component outlook
- 2.2.2. Diagnosis type outlook
- 2.3. Regional outlook
- 2.4. Competitive Insights
Chapter 3. Artificial Intelligence In Diagnostics Market Variables, Trends & Scope
- 3.1. Market Lineage Outlook
- 3.2. Market Dynamics
- 3.2.1. Market driver analysis
- 3.2.2. Market restraint analysis
- 3.2.3. Market opportunity analysis
- 3.2.4. Market challenges analysis
- 3.3. Artificial Intelligence In Diagnostics Market Analysis Tools
- 3.3.1. Industry Analysis - Porter's
- 3.3.1.1. Supplier power
- 3.3.1.2. Buyer power
- 3.3.1.3. Substitution threat
- 3.3.1.4. Threat of new entrant
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Economic landscape
- 3.3.2.3. Social landscape
- 3.3.2.4. Technological landscape
- 3.3.2.5. Environmental landscape
- 3.3.2.6. Legal landscape
- 3.4. Case Study Insights
Chapter 4. Artificial Intelligence In Diagnostics Market: Component Estimates & Trend Analysis
- 4.1. Component Market Share, 2025 & 2033
- 4.2. Segment Dashboard
- 4.3. Global Artificial Intelligence In Diagnostics Market, By Component Outlook
- 4.4. Software
- 4.4.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 4.5. Hardware
- 4.5.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 4.6. Services
- 4.6.1. Market estimates and forecast, 2021 to 2033 (USD Million)
Chapter 5. Artificial Intelligence In Diagnostics Market: Diagnosis Type Estimates & Trend Analysis
- 5.1. Diagnosis Type Market Share, 2025 & 2033
- 5.2. Segment Dashboard
- 5.3. Global Artificial Intelligence In Diagnostics Market, By Diagnosis Type Outlook
- 5.4. Cardiology
- 5.4.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.5. Oncology
- 5.5.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.6. Pathology
- 5.6.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.7. Radiology
- 5.7.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.8. Chest and Lung
- 5.8.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.9. Neurology
- 5.9.1. Market estimates and forecast, 2021 to 2033 (USD Million)
- 5.10. Others
- 5.10.1. Market estimates and forecast, 2021 to 2033 (USD Million)
Chapter 6. Artificial Intelligence In Diagnostics Market: Regional Estimates & Trend Analysis, By Component, By Diagnosis Type
- 6.1. Regional Market Share Analysis, 2025 & 2033
- 6.2. Regional Market Dashboard
- 6.3. Global Regional Market Snapshot
- 6.4. Market Size, & Forecasts Trend Analysis, 2021 to 2033:
- 6.5. North America
- 6.5.1. U.S.
- 6.5.1.1. Key country dynamics
- 6.5.1.2. Regulatory framework
- 6.5.1.3. Competitive scenario
- 6.5.1.4. U.S. market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.5.2. Canada
- 6.5.2.1. Key country dynamics
- 6.5.2.2. Regulatory framework
- 6.5.2.3. Competitive scenario
- 6.5.2.4. Canada market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.5.3. Mexico
- 6.5.3.1. Key country dynamics
- 6.5.3.2. Regulatory framework
- 6.5.3.3. Competitive scenario
- 6.5.3.4. Mexico market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6. Europe
- 6.6.1. UK
- 6.6.1.1. Key country dynamics
- 6.6.1.2. Regulatory framework
- 6.6.1.3. Competitive scenario
- 6.6.1.4. UK market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.2. Germany
- 6.6.2.1. Key country dynamics
- 6.6.2.2. Regulatory framework
- 6.6.2.3. Competitive scenario
- 6.6.2.4. Germany market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.3. France
- 6.6.3.1. Key country dynamics
- 6.6.3.2. Regulatory framework
- 6.6.3.3. Competitive scenario
- 6.6.3.4. France market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.4. Italy
- 6.6.4.1. Key country dynamics
- 6.6.4.2. Regulatory framework
- 6.6.4.3. Competitive scenario
- 6.6.4.4. Italy market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.5. Spain
- 6.6.5.1. Key country dynamics
- 6.6.5.2. Regulatory framework
- 6.6.5.3. Competitive scenario
- 6.6.5.4. Spain market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.6. Norway
- 6.6.6.1. Key country dynamics
- 6.6.6.2. Regulatory framework
- 6.6.6.3. Competitive scenario
- 6.6.6.4. Norway market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.7. Sweden
- 6.6.7.1. Key country dynamics
- 6.6.7.2. Regulatory framework
- 6.6.7.3. Competitive scenario
- 6.6.7.4. Sweden market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.6.8. Denmark
- 6.6.8.1. Key country dynamics
- 6.6.8.2. Regulatory framework
- 6.6.8.3. Competitive scenario
- 6.6.8.4. Denmark market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7. Asia Pacific
- 6.7.1. Japan
- 6.7.1.1. Key country dynamics
- 6.7.1.2. Regulatory framework
- 6.7.1.3. Competitive scenario
- 6.7.1.4. Japan market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7.2. China
- 6.7.2.1. Key country dynamics
- 6.7.2.2. Regulatory framework
- 6.7.2.3. Competitive scenario
- 6.7.2.4. China market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7.3. India
- 6.7.3.1. Key country dynamics
- 6.7.3.2. Regulatory framework
- 6.7.3.3. Competitive scenario
- 6.7.3.4. India market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7.4. Australia
- 6.7.4.1. Key country dynamics
- 6.7.4.2. Regulatory framework
- 6.7.4.3. Competitive scenario
- 6.7.4.4. Australia market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7.5. South Korea
- 6.7.5.1. Key country dynamics
- 6.7.5.2. Regulatory framework
- 6.7.5.3. Competitive scenario
- 6.7.5.4. South Korea market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.7.6. Thailand
- 6.7.6.1. Key country dynamics
- 6.7.6.2. Regulatory framework
- 6.7.6.3. Competitive scenario
- 6.7.6.4. Singapore market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.8. Latin America
- 6.8.1. Brazil
- 6.8.1.1. Key country dynamics
- 6.8.1.2. Regulatory framework
- 6.8.1.3. Competitive scenario
- 6.8.1.4. Brazil market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.8.2. Argentina
- 6.8.2.1. Key country dynamics
- 6.8.2.2. Regulatory framework
- 6.8.2.3. Competitive scenario
- 6.8.2.4. Argentina market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.9. MEA
- 6.9.1. South Africa
- 6.9.1.1. Key country dynamics
- 6.9.1.2. Regulatory framework
- 6.9.1.3. Competitive scenario
- 6.9.1.4. South Africa market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.9.2. Saudi Arabia
- 6.9.2.1. Key country dynamics
- 6.9.2.2. Regulatory framework
- 6.9.2.3. Competitive scenario
- 6.9.2.4. Saudi Arabia market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.9.3. UAE
- 6.9.3.1. Key country dynamics
- 6.9.3.2. Regulatory framework
- 6.9.3.3. Competitive scenario
- 6.9.3.4. UAE market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.9.4. Kuwait
- 6.9.4.1. Key country dynamics
- 6.9.4.2. Regulatory framework
- 6.9.4.3. Competitive scenario
- 6.9.4.4. Kuwait market estimates and forecasts, 2021 to 2033 (USD Million)
Chapter 7. Competitive Landscape
- 7.1. Competitor Growth Readiness Index (GRI), 2025
- 7.2. Competitor Capability Matrix, 2025
- 7.3. Company Categorization
- 7.4. Company Market Position Analysis
- 7.5. Strategy Mapping
- 7.6. Company Profiles/Listing
- 7.6.1. Key company market share analysis, 2025
- 7.6.2. Siemens Healthineers
- 7.6.2.1. Company overview
- 7.6.2.2. Financial performance
- 7.6.2.3. Product benchmarking
- 7.6.2.4. Strategic initiatives
- 7.6.3. Zebra Technologies Corp.
- 7.6.3.1. Company overview
- 7.6.3.2. Financial performance
- 7.6.3.3. Product benchmarking
- 7.6.3.4. Strategic initiatives
- 7.6.4. Riverain Technologies
- 7.6.4.1. Company overview
- 7.6.4.2. Financial performance
- 7.6.4.3. Product benchmarking
- 7.6.4.4. Strategic initiatives
- 7.6.5. Vuno, Inc.
- 7.6.5.1. Company overview
- 7.6.5.2. Financial performance
- 7.6.5.3. Product benchmarking
- 7.6.5.4. Strategic initiatives
- 7.6.6. Aidoc
- 7.6.6.1. Company overview
- 7.6.6.2. Financial performance
- 7.6.6.3. Product benchmarking
- 7.6.6.4. Strategic initiatives
- 7.6.7. NovaSignal Corporation (previously known as Neural Analytics, acquired by NeuraSignal, Inc.)
- 7.6.7.1. Company overview
- 7.6.7.2. Financial performance
- 7.6.7.3. Product benchmarking
- 7.6.7.4. Strategic initiatives
- 7.6.8. Koninklijke Philips N.V.
- 7.6.8.1. Company overview
- 7.6.8.2. Financial performance
- 7.6.8.3. Product benchmarking
- 7.6.8.4. Strategic initiatives
- 7.6.9. Digital Diagnostics, Inc.
- 7.6.9.1. Company overview
- 7.6.9.2. Financial performance
- 7.6.9.3. Product benchmarking
- 7.6.9.4. Strategic initiatives
- 7.6.10. GE Healthcare
- 7.6.10.1. Company overview
- 7.6.10.2. Financial performance
- 7.6.10.3. Product benchmarking
- 7.6.10.4. Strategic initiatives
- 7.6.11. AliveCor Inc.
- 7.6.11.1. Company overview
- 7.6.11.2. Financial performance
- 7.6.11.3. Product benchmarking
- 7.6.11.4. Strategic initiatives
- 7.6.12. F. Hoffmann-La Roche Ltd
- 7.6.12.1. Company overview
- 7.6.12.2. Financial performance
- 7.6.12.3. Product benchmarking
- 7.6.12.4. Strategic initiatives