Artificial intelligence diagnostics market is estimated to be valued at USD 2,207.8 Mn in 2025 and is expected to reach USD 8,481.6 Mn in 2032, exhibiting a compound annual growth rate (CAGR) of 21.2% from 2025 to 2032.
Artificial Intelligence (AI) diagnostics global market is growing at a rapid pace, spurred by the growing demand for faster, more precise, and affordable diagnostic solutions across healthcare systems globally. The rise of lifestyle diseases, an increase in healthcare expenses, and a worldwide shortage of doctors are compelling healthcare providers to implement AI-based diagnostic applications.
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Release of AI-Based Diagnostic Solutions by Qure.AI
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Integration of AI in Diagnostic Imaging by Siemens Healthineers
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The digital healthcare market is growing at a rapid pace, constantly showing untapped opportunities for entrepreneurs. The healthcare space holds large volumes of data from imaging, genomics, and diagnostics, which has led to the emergence of startups over recent years. Startups in personalized and connected healthcare are receiving recognition by enabling patients to track their health, allowing them to choose & manage their healthcare services.
In 2024, Axle Health raised $10 million in a Series A funding round. The round was led by F-Prime Capital, with participation from Y Combinator, Pear VC, and Light bank. Axle Health focuses on revolutionizing home healthcare using AI-powered logistics software.
Another factor which is driving the growth of the global artificial intelligence (AI) diagnostics market is the integration of AI in to the medical, and healthcare sector. For instance, Integration of AI into electronic medical records can provide multiple benefits and can significantly improve diagnostic algorithms, decision support, interoperability, flexibility, capturing physician-patient conversation.
For instance, Google collaborated with delivery networks for prediction modules to alert health risks such as heart failure. Machine learning solutions for IBM Watson, AllScripts, and Change Healthcare are using healthcare data to recommend personalized treatment options. Amazon Web Services provides a cloud computing tool that uses AI to extract and index data from clinical notes.
In the field of pathology, which is filled with large datasets consisting of types and subtypes of a disease specimen & biomarkers, it can be extremely complicated & exhausting for a human pathologist to keep up with changes. AI- based systems can work continuously and can be trained to record and analyze any number of specimens. The integration of AI in pathology with large datasets of genomics and biomarkers can help ease out the role of a pathologist in providing accurate and efficient diagnostics.
In 2024, significant advancements in artificial intelligence (AI) integration into pathology were achieved, particularly in the detection of metastatic breast cancer. A notable study developed a deep learning model utilizing magnetic resonance imaging (MRI) to predict the spread of breast cancer to axillary lymph nodes.
Managing and preventing or delaying the onset of chronic diseases can be a taxing & time-consuming task. AI-based data-driven technologies are enabling healthcare personnel to accurate and timely treatment, enabling a more proactive & preventive approach rather than a reactive one. AI can help provide an integrated care plan to better manage chronic ailments. Image processing, diagnostic findings, deep learning, and neural networks have experienced advancements over the past few years.
Based on Component, the Software Segment is expected to dominate the artificial intelligence (AI) market over the forecast period and this is attributed to the increasing integration of AI technology into the healthcare system.
Based on diagnostics Type, Cardiology Segment is expected to dominate the market over the forecast period and this is attributed to the increasing prevalence rate of cardiovascular disease worldwide.
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Increasing adoption of Artificial Intelligence (AI) in disease identification & diagnostics, and increasing investment in AI healthcare startups are factors expected to drive AI in diagnostics market demand. In addition, growing demand for reducing diagnostic costs, improving patient care, and reducing machine downtime are further accelerating usage of AI in diagnostics.
Increasing patient pool, ongoing pandemic, growing acceptance of cloud computing, and rising number of government programs supporting AI are among the key factors expected to drive the market in Asia Pacific. In addition, an increasing number of biopharmaceutical firms are applying AI to modernize the drug discovery process, with more AI applications being found in the field of diagnostics.
The United States dominates the global market for AI diagnostics market revenue, bolstered by high investments in healthcare technology, a mature AI startup ecosystem, and the support of both public and private sectors. Its superior digital infrastructure as well as implementation of AI in radiology, pathology, and genomics have fueled adoption in major hospital chains and research institutions. Regulatory advancements by the FDA for AI-based diagnostic solutions have further promoted innovation and commercialization.
China is quickly becoming a leading power in the AI diagnostics domain, driven by its huge patient base, government support, and vast data assets. The "Healthy China 2030" plan is an example of national efforts in AI-driven healthcare transformation. Major Chinese technology companies such as Alibaba and Tencent are also actively working on AI diagnostic platforms, with an emphasis on medical imaging and early disease detection.
| Report Coverage | Details | ||
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| Base Year: | 2024 | Market Size in 2025: | USD 2,207.8 Mn |
| Historical Data for: | 2020 To 2024 | Forecast Period: | 2025 To 2032 |
| Forecast Period 2025 to 2032 CAGR: | 21.2% | 2032 Value Projection: | USD 8,481.6 Mn |
| Geographies covered: |
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| Companies covered: |
Vuno Inc., CHC Healthcare Group, Aidoc, Imbio, Alivecor Inc., Digital Diagnostics, Retina AI, Canon Medical Systems USA, Healthy Io, Milliman Inc., GE Healthcare, Arterys, Alivecor Inc., Riverain, Lucid Health, Qure.AI, and Cardiologs, among others. |
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*Definition: By using AI algorithms to analyze vast amounts of medical data and identify patterns and relationships, general AI for medical diagnostics can transform the field of medicine, leading to improved patient outcomes and a more efficient and effective healthcare system. However, the development and deployment of AI in medical diagnostics are still in the early stages, and there are several technical, regulatory, and ethical challenges that must be overcome for the technology to reach its full potential.
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About Author
Komal Dighe is a Management Consultant with over 8 years of experience in market research and consulting. She excels in managing and delivering high-quality insights and solutions in Health-tech Consulting reports. Her expertise encompasses conducting both primary and secondary research, effectively addressing client requirements, and excelling in market estimation and forecast. Her comprehensive approach ensures that clients receive thorough and accurate analyses, enabling them to make informed decisions and capitalize on market opportunities.
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