Global Artificial Intelligence (AI) in Medical Market Growth (Status and Outlook) 2025-2031

The global Artificial Intelligence (AI) in Medical market size is predicted to grow from US$ 118330 million in 2025 to US$ 538600 million in 2031; it is expected to grow at a CAGR of 28.7% from 2025 to 2031.

Artificial Intelligence (AI) in the medical field refers to the use of machine learning, deep learning, natural language processing (NLP), and other technologies to assist healthcare professionals and institutions in improving diagnostic, treatment, and management efficiencies. AI encompasses a wide range of applications, such as medical data analysis, pathology diagnosis, image processing, patient monitoring, and personalized treatment. By analyzing large amounts of medical data, AI helps identify potential disease signs and provides fast, accurate diagnostic results, thereby improving treatment outcomes, reducing medical errors, and lowering operational costs.

The scope of AI products in the medical field is extensive and can be classified into the following key categories:

1. Medical Image Analysis: AI in medical imaging is primarily used to analyze X-rays, CT scans, MRI scans, etc., to assist doctors in identifying diseases such as tumors, fractures, and heart conditions. Using deep learning algorithms, AI can analyze images faster and more accurately than traditional methods, providing diagnostic support.

2. Disease Prediction and Early Diagnosis: AI can analyze patient history data to predict the potential risk of diseases. For example, AI can identify early signs of major diseases like cancer by analyzing genomic data.

3. Personalized Treatment Plans: AI analyzes a patient's genetic data, medical history, lifestyle, etc., to create personalized treatment plans, which is especially important in cancer treatment and chronic disease management.

4. Robot-Assisted Surgery: AI-assisted surgical robots enhance the precision of surgeries, reduce risks for doctors, and shorten patients' recovery times.

5. Smart Health Monitoring: AI, combined with wearable devices, can monitor a patient's vital signs, such as heart rate, blood pressure, and blood glucose levels in real-time, providing remote diagnostic support to doctors.

6. Natural Language Processing (NLP) and Electronic Health Records (EHR): AI uses NLP to extract key information from electronic health records, enabling more efficient decision-making for healthcare providers.

The market for Artificial Intelligence (AI) in healthcare is rapidly expanding, driven by several key factors:

1. Opportunities and Key Drivers:

Technological Advancements: Breakthroughs in deep learning, natural language processing, and big data analytics have made AI applications in healthcare more accurate and efficient. Improvements in hardware technology have enhanced AI's capabilities in areas like medical imaging and genomic data analysis.

Availability of Data: The digitization of electronic health records (EHR) and medical imaging data has provided vast amounts of data for training AI systems, enabling more widespread and precise applications of AI in healthcare.

Rising Healthcare Demands: The global aging population and the rise in chronic diseases are driving increasing demand for healthcare services. AI can address these demands by improving diagnostic efficiency and accuracy.

Government Support: Governments in various countries have introduced policies that encourage the application of AI in healthcare, offering funding and regulatory support to accelerate market growth.

2. Market Risks:

Data Privacy Issues: AI's reliance on large amounts of personal health data raises concerns over patient privacy and data security. Legal and regulatory delays could increase the risks of data breaches.

Technology Adoption Challenges: Despite AI's potential, widespread adoption is still hindered by high costs, particularly in developing countries, limiting the scalability of AI applications.

Ethical Concerns: AI decisions could be influenced by algorithmic biases, especially in diagnostic and pathological applications. Ensuring fairness and eliminating bias in AI decision-making is a critical ethical challenge.

3. Market Concentration:

The AI healthcare market is currently concentrated, with major players like IBM, Google, and Microsoft dominating the space, along with specialized AI companies such as Zebra Medical Vision and Aidoc. While there are emerging innovative companies, they face strong competitive pressures.

4. Downstream Demand Trends:

The demand for AI comes primarily from hospitals, clinics, and research institutions. As the need for accurate diagnostics and efficient treatments continues to grow, the range of AI applications is expanding. AI is especially in demand in early disease diagnosis and personalized treatment for conditions like cancer and heart disease.

5. Latest Technologies:

Multimodal Learning: Multimodal AI integrates multiple types of data (e.g., imaging, genomic data, medical history) to provide more comprehensive support for healthcare decision-making.

Augmented Reality (AR) and AI: In surgery, AR combined with AI can provide real-time image guidance, improving surgical precision.

AI-Assisted Drug Discovery: AI plays a significant role in drug development by predicting drug efficacy, screening candidate compounds, and accelerating the time-to-market for new drugs.

LPI (LP Information)' newest research report, the “Artificial Intelligence (AI) in Medical Industry Forecast” looks at past sales and reviews total world Artificial Intelligence (AI) in Medical sales in 2024, providing a comprehensive analysis by region and market sector of projected Artificial Intelligence (AI) in Medical sales for 2025 through 2031. With Artificial Intelligence (AI) in Medical sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Artificial Intelligence (AI) in Medical industry.

This Insight Report provides a comprehensive analysis of the global Artificial Intelligence (AI) in Medical landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Artificial Intelligence (AI) in Medical portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Artificial Intelligence (AI) in Medical market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Artificial Intelligence (AI) in Medical and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Artificial Intelligence (AI) in Medical.

This report presents a comprehensive overview, market shares, and growth opportunities of Artificial Intelligence (AI) in Medical market by product type, application, key players and key regions and countries.

Segmentation by Type:
Machine Learning Models
Natural Language Processing
Computer Vision
Robotics
Others

Segmentation by Application:
Medical Imaging & Diagnostics
Drug Discovery
Personalized Medicine
Healthcare Administration
Virtual Health Assistants

This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries

The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
IBM Watson Health
Siemens Healthineers
GE Healthcare
Aidoc
Zebra Medical Vision
PathAI
Google Health
Butterfly Network
Tempus
Arterys
Abbott Laboratories
Philips Healthcare
Medtronic
Canon Medical Systems
Johnson & Johnson
Nuance Communications
Veeva Systems
Babylon Health
AliveCor
Health Catalyst
Atomwise
Insilico Medicine
BenevolentAI
Cerner
Allscripts
Ada Health
Buoy Health

Please note: The report will take approximately 2 business days to prepare and deliver.