Artificial Intelligence in Oncology Market Report 2026

The artificial intelligence in oncology market size has grown exponentially in recent years. It will grow from $2.35 billion in 2025 to $3.13 billion in 2026 at a compound annual growth rate (CAGR) of 33.4%. The growth in the historic period can be attributed to increasing global cancer incidence rates, growth of oncology research initiatives, expansion of digital pathology adoption, rising use of data-driven cancer diagnostics, investments in advanced oncology infrastructure.

The artificial intelligence in oncology market size is expected to see exponential growth in the next few years. It will grow to $10.25 billion in 2030 at a compound annual growth rate (CAGR) of 34.5%. The growth in the forecast period can be attributed to increasing adoption of precision oncology solutions, rising demand for personalized cancer therapies, expansion of ai use in clinical oncology trials, growing integration of genomics with ai platforms, increasing investments in oncology-focused ai startups. Major trends in the forecast period include increasing adoption of AI-based cancer detection tools, rising use of ai in treatment planning optimization, growing integration of ai in drug discovery and development, expansion of predictive oncology analytics, enhanced focus on precision oncology applications.

The increasing occurrence of cancer cases is anticipated to drive the growth of the AI in oncology market in the coming years. Cancer is a complex set of diseases marked by the uncontrolled growth and division of abnormal cells within the body. Incorporating AI into oncology has the potential to transform cancer care by making it more precise, personalized, and efficient. For example, in 2023, according to a report by the American Cancer Society Inc., a US-based voluntary health organization, the estimated number of new cancer cases rose from 1.8 million to 1.9 million. Consequently, the rising occurrence of cancer cases is fueling the growth of the AI in oncology market.

Major companies in the AI in oncology market are concentrating on developing advanced software solutions, including cloud-based platforms, to improve effectiveness and offer enhanced services. Cloud-based software is vital for AI applications in oncology as it provides a scalable, flexible, and accessible environment for processing and analyzing large amounts of medical data. For example, in March 2023, Illumina Inc., a US-based biotechnology company, introduced Connected Insights, a new cloud-based software that enables tertiary analysis for oncology applications. By integrating external knowledge bases, Connected Insights simplifies the interpretation and reporting of results from various assay types, allowing laboratories to expand the use of NGS (Next-Generation Sequencing) and accelerate clinical reporting turnaround times.

In May 2024, Lunit, a South Korea-based medical solutions company, acquired Volpara Health Technologies for $193 million. This acquisition by Lunit aims to establish a strong partnership in the cancer diagnostics sector, particularly in the U.S. market. By leveraging their combined expertise, Lunit intends to advance its AI-powered solutions for early cancer detection and enhance patient care. Volpara Health Technologies is a New Zealand-based healthcare software company that develops and provides breast cancer detection and diagnostic tools.

Major companies operating in the artificial intelligence in oncology market are Azra AI, IBM Corporation, Siemens Healthcare GmbH, GE HealthCare, NVIDIA Corporation, Digital Diagnostics Inc., ConcertAI Inc., PathAI Inc., Median Technologies SA, Kheiron Medical Technologies Ltd, Tempus Labs Inc., Paige AI Inc., Prognos Health Inc., Enlitic, Inspirata Inc., Proscia Inc., Deep 6 AI Inc., Intel Corporation, Zebra Medical Vision, Ibex Medical Analytics, Nanox Imaging Ltd., Berg LLC.

North America was the largest region in the AI in oncology market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence in oncology market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence in oncology market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs are influencing the artificial intelligence in oncology market by increasing costs of imported imaging equipment, genomic sequencing hardware, high-performance computing systems, and AI-enabled diagnostic devices. Oncology centers and pharmaceutical companies in North America and Europe are most affected due to reliance on imported advanced technologies, while Asia-Pacific faces higher costs for exporting AI-based oncology solutions. These tariffs are increasing R&D and deployment expenses and slowing technology adoption in smaller oncology centers. However, they are also encouraging domestic innovation, localized manufacturing of oncology devices, and increased investment in software-centric AI oncology platforms.

The artificial intelligence in oncology market research report is one of a series of new reports that provides artificial intelligence in oncology market statistics, including artificial intelligence in oncology industry global market size, regional shares, competitors with a artificial intelligence in oncology market share, detailed artificial intelligence in oncology market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence in oncology industry. This artificial intelligence in oncology market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

Artificial intelligence in oncology involves the use of AI technologies and methods in cancer diagnosis, treatment, research, and patient management. The aim of AI in oncology is to enhance outcomes for cancer patients by utilizing computational approaches to detect patterns, forecast outcomes, and assist in evidence-based decision-making throughout the entire spectrum of cancer care.

The primary components of artificial intelligence in oncology include software solutions, hardware, and services. Software solutions in oncology utilize artificial intelligence (AI) to improve different aspects of cancer diagnosis, treatment, and research. The treatment types encompass chemotherapy, radiotherapy, immunotherapy, and others. The cancer types include breast cancer, lung cancer, prostate cancer, colorectal cancer, brain tumors, and others. These solutions are applied in areas such as cancer detection, drug discovery, and drug development, and are used by various end-users including hospitals, diagnostic centers, pharmaceutical companies, research institutes, and others.

The artificial intelligence in oncology market consists of revenues earned by entities by providing services such as surgery, targeted therapy, and stem cell transplantation. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence in the oncology market also includes sales of edge devices, storage devices, field-programmable gate arrays (FPGA), and tensor processing units (TPU). Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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