AI In Oncology Market Overview

The AI in oncology market was valued at USD 6.0 billion in 2025. It is estimated at USD 8.3 billion in 2026 and is projected to reach USD 38.9 billion by 2033, a CAGR of 24.8% from 2026 to 2033. That is roughly a 4.7x expansion in seven years, and it signals that AI is becoming a core layer of cancer care rather than an experimental add-on. North America led in 2025 with a 45.8% revenue share, while Asia Pacific is expected to grow the fastest.

Key Market Dynamics & Segments

The market is segmented by component type, cancer type, application, end use and region. Each segment has a clear leader today and a different segment growing faster behind it.

Component type. Hardware led in 2025 with a 39.4% share. AI is embedded in imaging systems and medical devices that providers already buy, so hardware captured the early revenue. Software solutions are expected to grow fastest from 2026 to 2033. Software tools predict brain, breast, liver, lung and prostate cancer, and Grand View Research says they can be more accurate than clinicians in some cases. Value is shifting from the machine to the algorithm running on it, and companies choosing where to build their offering should note that.

Cancer type. Breast cancer held the largest share, about 21% in 2025. The American Cancer Society expects 316,950 new invasive breast cancer cases in the U.S. in 2025. Prostate cancer is expected to register the fastest CAGR, even though the same society expects a nearly identical 313,780 new U.S. prostate cases in 2025. Breast cancer leads because mammography AI is more mature. The near parity in case volume suggests prostate detection tools, such as MRI-based AI, have room to catch up quickly. Quibim's January 2024 launch of QP-Prostate shows companies are already moving in.

Application. Diagnostics led with a 37% share, because diagnosis is the starting point for every treatment decision. Research and development is projected to grow fastest as machine learning and deep learning move into drug discovery, target identification and clinical trial design. In practice, AI is expanding from detecting cancer to helping develop the drugs that treat it.

End use. Hospitals dominated with a 48% share and are also expected to be the fastest-growing end user. Adoption is concentrating where clinical workflows, imaging data and patient volume already exist. In November 2024, for example, IDIBAPS-Hospital Clínic Barcelona unveiled an AI tool to support prostate cancer diagnosis.

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Regional Picture

North America's lead rests on developed digital infrastructure, favorable regulatory and reimbursement policies, and government initiatives. The U.S. holds the largest share in the region, and the FDA had authorized, cleared or approved over 690 AI-enabled devices as of its December 2023 factsheet.

Asia Pacific has the biggest long-term opportunity. GLOBOCAN estimated 19.9 million new cancer cases worldwide in 2022, and Asia Pacific accounted for 9.8 million of them, nearly half. India recorded more than 1.4 million new cases that year, and China holds the largest regional share.

Europe is growing on the shift toward value-based healthcare. Germany leads, driven by AI adoption among health insurers and in medical imaging. In the UK, NHS adoption is a key driver, including the April 2025 launch of Qure.ai's chest CT service across five imaging sites in four NHS trusts.

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Major Industry Players

The competitive landscape mixes imaging giants, chipmakers and AI-native specialists. Grand View Research profiles Azra AI, iCAD, Siemens Healthcare, Intel, GE HealthCare, NVIDIA, Digital Diagnostics, ConcertAI, Median Technologies, PathAI and MVision AI.

Their strategies fall into three broad patterns.

Partnerships and integrations. In April 2025, iCAD integrated its ProFound AI Breast Health Suite into Microsoft's Precision Imaging Network, giving radiologists cloud-hosted access aimed at better detection and fewer false positives. In October 2023, Philips partnered with Quibim to launch AI-powered MR prostate screening and reporting.

Acquisitions and data assets. In December 2023, ConcertAI acquired CancerLinQ, formerly an ASCO subsidiary, and ASCO signed a multiyear cooperation agreement with it. The deal shows that real-world oncology data is now as strategic as the algorithms trained on it.

Geographic expansion and regulatory wins. Lunit signed a supply agreement with Seha Virtual Hospital in 2023 to bring mammography AI to the Middle East. MVision AI's Contour+ was cleared in the UAE in April 2025. Roche received FDA Breakthrough Device Designation in April 2025 for an AI-powered companion diagnostic for advanced non-small cell lung cancer, which shows how closely diagnostics and drug development are now linked.

Explore the full list of profiled companies operating in this market with recent strategic initiatives

Core Growth Drivers & Restraints

Growth Drivers

Rising cancer prevalence. The NIH estimated that about 2.0 million people in the U.S. would be diagnosed with cancer in 2023. Heavier caseloads put pressure on radiologists and pathologists, and AI helps by taking over routine work such as quantification, segmentation and pattern recognition before a specialist reviews the case.

Advances in diagnostics and infrastructure. Better computing power, learning algorithms, cloud storage and electronic health record data have made AI systems more accurate. They draw on ultrasound, MRI, CT and PET imaging to support earlier diagnosis. In Grand View Research's survey of researchers, about one-third believed cancer radiology would benefit most from AI over the next decade, and 27.02% chose pathology. The survey had a 4.12% response rate (1,030 of 25,000 invited), so it reflects expert opinion rather than market data.

Precision medicine. In January 2024, Penn Medicine researchers created iStar, an AI tool that analyzes gene activity in medical images and can help identify patients likely to respond to immunotherapy.

Regulatory and funding momentum. The FDA approved the DermaSensor skin cancer detection device in January 2024, and its 2021 action plan for AI/ML-based Software as a Medical Device gave the industry a clearer path. Programs like Tempus+, launched in October 2022, use real-world data to support collaborative research across institutions including Stanford Cancer Center and Baylor College of Medicine.

Restraints

The biggest restraint is cost. Grand View Research cites a Folio3 estimate that implementing AI in healthcare ranges from USD 20,000 to USD 1,000,000. A minimum viable product alone costs between USD 8,000 and USD 15,000. Integrating hardware and software, building specialist teams, ongoing upgrades, maintenance and staff training add further expense.

Government spending on AI technologies is low, so hospitals and private buyers often carry most of the cost. That favors well-funded institutions and may slow adoption in smaller or resource-limited settings.

What This Means for the Market

The trends point in one direction. Hospitals are both the biggest and the fastest-growing buyers. Spending is expected to shift from hardware toward software, and from diagnostics toward drug discovery. Asia Pacific's cancer burden positions it as the region to watch.

Companies that combine strong algorithms with proprietary data, regulatory clearances and cost-efficient deployment look best placed to capture the next phase of growth.