The U.S. AI in oncology market size was estimated at USD 891.90 million in 2023 and is projected to hit around USD 10,745.55 million by 2033, growing at a CAGR of 28.26% during the forecast period from 2024 to 2033.
The U.S. AI in Oncology market is characterized by its dynamic and rapidly evolving landscape, driven by the intersection of cutting-edge technology and the imperative need for innovative solutions in cancer care. This market encompasses a wide array of applications, spanning from early detection and diagnosis to treatment planning and personalized medicine. Leveraging the power of artificial intelligence (AI) and machine learning, healthcare providers are empowered to analyze vast amounts of medical data with unparalleled accuracy and efficiency. The market is propelled by key drivers such as the precision medicine revolution, which enables oncologists to tailor treatment strategies based on the unique genetic makeup of each patient. Furthermore, AI-powered diagnostic imaging techniques have significantly enhanced diagnostic accuracy by detecting subtle abnormalities that may evade human detection. Additionally, the integration of AI-driven solutions into clinical workflows streamlines administrative tasks, reduces manual errors, and optimizes resource utilization. Despite regulatory considerations and challenges regarding data privacy and security, the U.S. AI in Oncology market remains poised for continued growth and innovation, promising a future where cancer diagnosis and treatment are revolutionized by advanced AI technologies.
Report Attribute | Details |
Market Size in 2024 | USD 1,143.95 million |
Market Size by 2033 | USD 10,745.55 million |
Growth Rate From 2024 to 2033 | CAGR of 28.26% |
Base Year | 2023 |
Forecast Period | 2024 to 2033 |
Segments Covered | Component, cancer type, application, end-use |
Market Analysis (Terms Used) | Value (US$ Million/Billion) or (Volume/Units) |
Report Coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
Key Companies Profiled | Azra AI; iCAD, Inc.; IBM; Siemens Healthcare GmbH; Intel Corporation; GE HealthCare; NVIDIA Corporation; Digital Diagnostics Inc.; ConcertAI; Median Technologies; PathAI |
The growth of the U.S. AI in Oncology market is fueled by several key factors. Firstly, the increasing demand for personalized medicine has propelled the adoption of AI-driven solutions in oncology. These technologies enable healthcare providers to tailor treatment plans based on the unique genetic makeup of each patient, leading to more effective therapies and improved outcomes. Additionally, advancements in diagnostic imaging, powered by AI algorithms, have revolutionized the early detection and diagnosis of cancer, allowing for prompt intervention and better prognosis. Moreover, the integration of AI into clinical workflows has streamlined processes, enhancing operational efficiency and resource utilization within healthcare facilities. These factors, combined with ongoing research and development efforts, contribute to the rapid growth and expansion of the U.S. AI in Oncology market.
Based on components, hardware dominated the market with a revenue share of 39.14% in 2023 and is anticipated to continue its dominance over the forecast period. AI hardware refers to physical components and systems tailored to meet the computational demands of AI algorithms. Medical linear accelerators, crucial in oncology for radiotherapy, fall within this scope. For example, Varian's Ethos therapy, an AI-powered adaptive radiotherapy treatment system with a linear accelerator, obtained regulatory clearances in 2019 and 2020. Ethos therapy enhances radiotherapy by providing adaptive treatments within a 15-minute time slot. The growing demand for AI-powered diagnostic solutions in automated detection systems is expected to support the delivery of improved diagnostic precision while interpreting medical images of a patient.
In addition, the growing demand for hardware platforms with high computing power to operate AI-based software contributes to segment growth. The software solutions segment is anticipated to witness the fastest CAGR from 2024 to 2033. The increasing adoption of AI software solutions by healthcare providers and payers operating in oncology is one of the major factors fueling the segment growth. Software solutions are highly effective at predicting various types of cancer, including brain, breast, liver, lung, and prostate cancer. They offer better accuracy compared to clinicians. Hence, numerous key players are focusing on developing & launching new tools and platforms, increasing the competition in the market.
Based on cancer type, the others segment held the largest revenue share of 25.14% in 2023 and is anticipated to grow at a lucrative CAGR from 2024 to 2033. The dominance of this segment is attributed to increasing prevalence of kidney cancer. According to the Global Cancer Observatory, kidney cancer is among the top 10 types of cancer. Some of the causes for this cancer type include inherited syndromes, high blood pressure, obesity, smoking, old age, long-term dialysis, and a family history of kidney cancer. Common diagnosing techniques include blood tests and imaging procedures, such as CT, Magnetic Resonance Imaging (MRI), and ultrasound. In addition, various awareness programs undertaken by public & private organizations to improve awareness about kidney cancer are expected to support market growth.
The prostate cancer segment is expected to register the fastest CAGR from 2024 to 2033. Prostate cancer generally affects 13 out of every 100 men in the U.S., according to the data published by the CDC. Moreover, according to the National Cancer Institute, in 2023, approximately 288,300 new prostate cancer cases were diagnosed. Some of the risk factors for prostate cancer include age, family history of prostate cancer, diet, smoking, obesity, chemical exposure, and vasectomy. Obesity has a substantial impact on men suffering from advanced & aggressive (fast-growing) prostate cancer. According to certain studies, obesity is also linked with higher chances of death.
The hospitals segment dominated the market with a revenue share of 48.25% in 2023 owing to the rising demand for AI applications to revolutionize medicine and advance research, diagnostics, & cancer treatment. Furthermore, the growing adoption of AI in pathology solutions, especially for cancer diagnostics, is a major market driver. The hospitals segment is expected to grow at the fastest CAGR from 2024 to 2033 due to the rising adoption of AI-powered solutions.
A rising number of companies entering the market to cater to cancer care in hospitals, and positive responses from patients, are expected to boost the market during the forecast period. According to the AI Multiple reports, approximately 12 million individuals in the U.S. are misdiagnosed, of which 44% are misdiagnosed with cancer. The most misdiagnosed cancers are breast cancer, prostate cancer, and thyroid cancer. Hence, integrating AI-powered algorithms in cancer therapy is anticipated to flourish in the hospital segment over the upcoming decade.
The following are the leading companies in the U.S. AI in oncology market. These companies collectively hold the largest market share and dictate industry trends. Financials, strategy maps & products of these U.S. AI in oncology companies are analyzed to map the supply network.
This report forecasts revenue growth at country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Nova one advisor, Inc. has segmented the U.S. AI In Oncology market.
By Component Type
By Cancer Type
By Application
By End-use
Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.2. Segment Definitions
1.2.1. Component
1.2.2. Cancer Type
1.2.3. Application
1.2.4. End-use
1.2.5. Country scope
1.2.6. Estimates and forecasts timeline
1.3. Research Methodology
1.4. Information Procurement
1.4.1. Purchased database
1.4.2. nova one advisor internal database
1.4.3. Secondary sources
1.4.4. Primary research
1.4.5. Details of primary research
1.4.5.1. Data for primary interviews in U.S.
1.5. Information or Data Analysis
1.5.1. Data analysis models
1.6. Market Formulation & Validation
1.7. Model Details
1.7.1. Commodity flow analysis (Model 1)
1.7.2. Approach 1: Commodity flow approach
1.8. List of Secondary Sources
1.9. List of Primary Sources
1.10. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Component outlook
2.2.2. Cancer type outlook
2.2.3. Application outlook
2.2.4. End-use outlook
2.3. Competitive Insights
Chapter 3. U.S. AI in Oncology Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.1.1. Increasing demand for early detection and classification of cancer
3.2.1.1.1. Case study 1
3.2.1.1.2. Case study 2
3.2.1.2. Increasing prevalence of cancer
3.2.1.2.1. Breast
3.2.1.2.2. Barain & CNS
3.2.1.2.3. Kidney
3.2.1.2.4. Non-Hodgkin lymphoma
3.2.1.2.5. Bladder
3.2.1.2.6. Colon & rectum
3.2.1.2.7. Prostate
3.2.1.2.8. Case Study 3
3.2.1.3. Rising adoption of precision medicine
3.2.2. Market restraint analysis
3.2.2.1. High procurement and implementation cost
3.2.2.2. Lack of skilled workforce
3.3. U.S. AI in Oncology Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.2. PESTEL Analysis
3.4. Regulatory Framework
3.5. Impact of COVID-19
Chapter 4. U.S. AI in Oncology Market: Component Estimates & Trend Analysis
4.1. Component Market Share, 2021 & 2033
4.2. Segment Dashboard
4.3. U.S. AI in Oncology Market by Component Outlook
4.4. Hardware
4.4.1. Market estimates and forecasts, 2021 & 2033
4.5. Software solutions
4.5.1. Market estimates and forecasts, 2021 & 2033
4.6. Services
4.6.1. Market estimates and forecasts, 2021 & 2033
Chapter 5. U.S. AI in Oncology Market: Cancer Type Estimates & Trend Analysis
5.1. Cancer Type Market Share, 2021 & 2033
5.2. Segment Dashboard
5.3. U.S. AI in Oncology Market by Cancer Type Outlook
5.4. Breast Cancer
5.4.1. Market estimates and forecasts, 2021 & 2033
5.5. Lung Cancer
5.5.1. Market estimates and forecasts, 2021 & 2033
5.6. Prostate Cancer
5.6.1. Market estimates and forecasts, 2021 & 2033
5.7. Colorectal Cancer
5.7.1. Market estimates and forecasts, 2021 & 2033
5.8. Brain Tumor
5.8.1. Market estimates and forecasts, 2021 & 2033
5.9. Others
5.9.1. Market estimates and forecasts, 2021 & 2033
Chapter 6. U.S. AI in Oncology Market: Application Estimates & Trend Analysis
6.1. Application Market Share, 2021 & 2033
6.2. Segment Dashboard
6.3. U.S. AI in Oncology Market by Application Outlook
6.4. Diagnostics
6.4.1. Market estimates and forecasts, 2021 & 2033
6.5. Radiation Therapy
6.5.1. Market estimates and forecasts, 2021 & 2033
6.6. Research & Development
6.6.1. Market estimates and forecasts, 2021 & 2033
6.7. Chemotherapy
6.7.1. Market estimates and forecasts, 2021 & 2033
6.8. Immunotherapy
6.8.1. Market estimates and forecasts, 2021 & 2033
Chapter 7. U.S. AI in Oncology Market: End-use Estimates & Trend Analysis
7.1. End-use Market Share, 2021 & 2033
7.2. Segment Dashboard
7.3. U.S. AI in Oncology Market by End-use Outlook
7.4. Hospitals
7.4.1. Market estimates and forecasts, 2021 & 2033
7.5. Surgical Centers & Medical Institutes
7.5.1. Market estimates and forecasts, 2021 & 2033
7.6. Others
7.6.1. Market estimates and forecasts, 2021 & 2033
Chapter 8. Competitive Landscape
8.1. Recent Developments & Impact Analysis, By Key Market Participants
8.2. Company/Competition Categorization
8.3. Vendor Landscape
8.3.1. List of key distributors and channel partners
8.3.2. Key customers
8.3.3. Key company market share analysis, 2023
8.4. Company Profiles
8.4.1. Azra AI
8.4.1.1. Company overview
8.4.1.2. Financial performance
8.4.1.3. Product benchmarking
8.4.1.4. Strategic initiatives
8.4.2. iCAD, Inc.
8.4.2.1. Company overview
8.4.2.2. Financial performance
8.4.2.3. Product benchmarking
8.4.2.4. Strategic initiatives
8.4.3. IBM
8.4.3.1. Company overview
8.4.3.2. Financial performance
8.4.3.3. Product benchmarking
8.4.3.4. Strategic initiatives
8.4.4. Siemens Healthcare GmbH
8.4.4.1. Company overview
8.4.4.2. Financial performance
8.4.4.3. Product benchmarking
8.4.4.4. Strategic initiatives
8.4.5. Intel Corporation
8.4.5.1. Company overview
8.4.5.2. Financial performance
8.4.5.3. Product benchmarking
8.4.5.4. Strategic initiatives
8.4.6. GE HealthCare
8.4.6.1. Company overview
8.4.6.2. Financial performance
8.4.6.3. Product benchmarking
8.4.6.4. Strategic initiatives
8.4.7. NVIDIA Corporation
8.4.7.1. Company overview
8.4.7.2. Financial performance
8.4.7.3. Product benchmarking
8.4.7.4. Strategic initiatives
8.4.8. Digital Diagnostics Inc.
8.4.8.1. Company overview
8.4.8.2. Financial performance
8.4.8.3. Product benchmarking
8.4.8.4. Strategic initiatives
8.4.9. ConcertAI
8.4.9.1. Company overview
8.4.9.2. Financial performance
8.4.9.3. Product benchmarking
8.4.9.4. Strategic initiatives
8.4.10. Median Technologies
8.4.10.1. Company overview
8.4.10.2. Financial performance
8.4.10.3. Product benchmarking
8.4.10.4. Strategic initiatives
8.4.11. PathAI
8.4.11.1. Company overview
8.4.11.2. Financial performance
8.4.11.3. Product benchmarking
8.4.11.4. Strategic initiatives