세계의 종양학 AI 시장(-2032년) : 컴포넌트별, 암 유형별, 기술별, 용도별, 최종 사용자별, 지역별 분석

According to Stratistics MRC, the Global AI in Oncology Market is accounted for $3.2 billion in 2025 and is expected to reach $21.7 billion by 2032 growing at a CAGR of 31.4% during the forecast period. Artificial Intelligence (AI) in oncology refers to the use of advanced computational algorithms and machine learning models to enhance cancer detection, diagnosis, treatment planning, and patient monitoring. By analyzing large and complex datasets such as medical images, genomic profiles, and clinical records, AI systems can identify subtle patterns and predict disease progression more accurately than traditional methods. In oncology, AI aids in early tumor detection, personalized therapy selection, and drug discovery, improving overall treatment outcomes. It also supports radiologists and oncologists in making data-driven clinical decisions, ultimately advancing precision medicine and patient-centered cancer care.

Market Dynamics:

Driver:

Growing oncology data availability

Clinical records genomic profiles and imaging datasets are expanding rapidly across hospitals research centers and biobanks. Platforms use structured and unstructured data to train models for early detection risk stratification and therapy selection. Integration with EHRs pathology systems and radiology archives enhances model accuracy and clinical relevance. Demand for scalable and data-rich platforms is rising across precision oncology and population health initiatives. These dynamics are propelling platform deployment across AI-enabled cancer care ecosystems.

Restraint:

High cost of implementation and integration

Enterprises face challenges in aligning legacy systems with AI engines and ensuring interoperability across clinical workflows. Infrastructure upgrades data harmonization and staff training add complexity and cost to deployment. Lack of standardized protocols and reimbursement frameworks further delays adoption across hospitals and research institutions. Vendors must offer modular solutions cloud-native architecture and integration support to overcome these barriers. These constraints continue to hinder platform maturity across resource-constrained and compliance-sensitive environments.

Opportunity:

Personalized medicine and treatment optimization

Models predict tumor response identify biomarkers and guide therapy selection based on patient-specific data. Integration with genomic sequencing immunoprofiling and clinical trials enhances precision and outcome tracking. Demand for adaptive and explainable AI is rising across breast lung and colorectal cancer programs. Enterprises align AI strategies with value-based care clinical decision support and drug development goals. These trends are fostering growth across personalized and outcome-driven oncology platforms.

Threat:

Privacy, security and ethical concerns

Sensitive patient data genomic information and treatment records require robust encryption consent management and auditability. Enterprises face challenges in meeting HIPAA GDPR and regional data protection laws while maintaining model performance. Lack of transparency algorithmic bias and unclear accountability degrade stakeholder confidence and clinical adoption. Vendors must invest in governance dashboards ethical AI frameworks and stakeholder engagement to address these risks. These limitations continue to constrain platform deployment across regulated and high-stakes oncology environments.

Covid-19 Impact:

The pandemic disrupted cancer screening clinical trials and oncology workflows across global healthcare systems. Lockdowns delayed diagnosis and treatment while increasing demand for remote monitoring and digital decision support. AI platforms scaled rapidly to support triage virtual tumor boards and imaging analysis across teleoncology programs. Investment in cloud infrastructure real-time analytics and decentralized trials surged across public and private sectors. Public awareness of cancer risk and digital health tools increased across policy and consumer circles.

The machine learning segment is expected to be the largest during the forecast period

The machine learning segment is expected to account for the largest market share during the forecast period due to its versatility scalability and performance across oncology workflows. Models support image classification risk prediction and treatment recommendation using supervised and unsupervised learning techniques. Integration with radiomics genomics and clinical data enhances accuracy and generalizability across cancer types. Demand for adaptive and explainable ML is rising across diagnostics drug discovery and clinical decision support. Vendors offer modular engines APIs and visualization tools to support cross-functional adoption and performance tracking.

The lung cancer segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the lung cancer segment is predicted to witness the highest growth rate as AI platforms expand across early detection staging and therapy optimization. Models analyze CT scans pathology slides and molecular data to identify nodules predict progression and guide immunotherapy. Integration with screening programs clinical trials and real-world evidence enhances impact and scalability. Demand for scalable and high-accuracy solutions is rising across public health oncology and pharmaceutical research. Vendors offer AI-powered imaging tools biomarker discovery engines and decision support modules tailored to lung cancer workflows.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its research infrastructure clinical adoption and regulatory engagement across AI in oncology. Enterprises deploy platforms across hospitals cancer centers and pharmaceutical firms to enhance diagnostics and treatment planning. Investment in cloud migration data governance and workforce development supports scalability and compliance. Presence of leading vendors academic institutions and policy frameworks drives ecosystem maturity and innovation. Firms align AI strategies with FDA guidance payer models and precision medicine initiatives.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as cancer burden healthcare digitization and AI investment converge across regional economies. Countries like China India Japan and South Korea scale platforms across screening research and clinical oncology programs. Government-backed initiatives support infrastructure development startup incubation and public-private partnerships across cancer innovation. Local providers offer cost-effective culturally adapted and mobile-first solutions tailored to regional needs. Demand for scalable and inclusive oncology infrastructure is rising across urban and rural populations.

Key players in the market

Some of the key players in AI in Oncology Market include Siemens Healthineers AG, GE HealthCare Technologies Inc., Medtronic plc, IBM Corporation, Google LLC, Microsoft Corporation, NVIDIA Corporation, Azra AI Inc., ConcertAI LLC, PathAI Inc., Median Technologies SA, Tempus Labs Inc., Owkin Inc., Freenome Holdings Inc. and Paige.AI Inc.

Key Developments:

In July 2025, Siemens Healthineers signed a $50 million value partnership with Prisma Health, South Carolina's largest hospital system. The agreement expanded their 10-year collaboration to include AI-powered oncology solutions, notably the deployment of the Ethos radiotherapy system from Varian. The system enables adaptive therapy planning using real-time imaging and artificial intelligence.

In July 2024, GE HealthCare signed an agreement to acquire Intelligent Ultrasound Group PLC's clinical AI software business for approximately $51 million. The acquisition added real-time image recognition capabilities to GE's ultrasound portfolio, supporting oncology diagnostics in OBGYN and abdominal imaging. It aligned with GE's precision care strategy to improve exam accuracy and efficiency.

Components Covered:

• Software Solutions
• Hardware
• Services

Cancer Types Covered:

• Breast Cancer
• Lung Cancer
• Prostate Cancer
• Colorectal Cancer
• Cervical Cancer
• Other Cancer Types

Technologies Covered:

• Machine Learning
• Deep Learning
• Natural Language Processing
• Computer Vision for Radiomics and Histopathology
• AI-Driven Genomic Profiling and Biomarker Discovery
• Other Technologies

Applications Covered:

• Diagnosis & Screening
• Treatment Planning & Monitoring
• Drug Discovery & Development
• Genomic Profiling
• Prognostics & Risk Stratification
• Other Applications

End Users Covered:

• Hospitals
• Oncology Clinics
• Research Institutes
• Biopharmaceutical & Biotechnology Companies
• Diagnostic Laboratories
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • 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 2024, 2025, 2026, 2028, and 2032
• 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
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • 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 AI in Oncology Market, By Component

• 5.1 Introduction
• 5.2 Software Solutions
• 5.3 Hardware
• 5.4 Services

6 Global AI in Oncology Market, By Cancer Type

• 6.1 Introduction
• 6.2 Breast Cancer
• 6.3 Lung Cancer
• 6.4 Prostate Cancer
• 6.5 Colorectal Cancer
• 6.6 Cervical Cancer
• 6.7 Other Cancer Types

7 Global AI in Oncology Market, By Technology

• 7.1 Introduction
• 7.2 Machine Learning
• 7.3 Deep Learning
• 7.4 Natural Language Processing
• 7.5 Computer Vision for Radiomics and Histopathology
• 7.6 AI-Driven Genomic Profiling and Biomarker Discovery
• 7.7 Other Technologies

8 Global AI in Oncology Market, By Application

• 8.1 Introduction
• 8.2 Diagnosis & Screening
• 8.3 Treatment Planning & Monitoring
• 8.4 Drug Discovery & Development
• 8.5 Genomic Profiling
• 8.6 Prognostics & Risk Stratification
• 8.7 Other Applications

9 Global AI in Oncology Market, By End User

• 9.1 Introduction
• 9.2 Hospitals
• 9.3 Oncology Clinics
• 9.4 Research Institutes
• 9.5 Biopharmaceutical & Biotechnology Companies
• 9.6 Diagnostic Laboratories
• 9.7 Other End Users

10 Global AI in Oncology Market, By Geography

• 10.1 Introduction
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
  • 10.2.3 Mexico
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 Italy
  • 10.3.4 France
  • 10.3.5 Spain
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 Japan
  • 10.4.2 China
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 New Zealand
  • 10.4.6 South Korea
  • 10.4.7 Rest of Asia Pacific
• 10.5 South America
  • 10.5.1 Argentina
  • 10.5.2 Brazil
  • 10.5.3 Chile
  • 10.5.4 Rest of South America
• 10.6 Middle East & Africa
  • 10.6.1 Saudi Arabia
  • 10.6.2 UAE
  • 10.6.3 Qatar
  • 10.6.4 South Africa
  • 10.6.5 Rest of Middle East & Africa

11 Key Developments

• 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 11.2 Acquisitions & Mergers
• 11.3 New Product Launch
• 11.4 Expansions
• 11.5 Other Key Strategies

12 Company Profiling

• 12.1 Siemens Healthineers AG
• 12.2 GE HealthCare Technologies Inc.
• 12.3 Medtronic plc
• 12.4 IBM Corporation
• 12.5 Google LLC
• 12.6 Microsoft Corporation
• 12.7 NVIDIA Corporation
• 12.8 Azra AI Inc.
• 12.9 ConcertAI LLC
• 12.10 PathAI Inc.
• 12.11 Median Technologies SA
• 12.12 Tempus Labs Inc.
• 12.13 Owkin Inc.
• 12.14 Freenome Holdings Inc.
• 12.15 Paige.AI Inc.