The Market Reports

Synopsis
The global market for Artificial Intelligence (AI) in Medical was estimated to be worth US$ 100370 million in 2024 and is forecast to a readjusted size of US$ 524550 million by 2031 with a CAGR of 27.7% during the forecast period 2025-2031.
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.
This report aims to provide a comprehensive presentation of the global market for Artificial Intelligence (AI) in Medical, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Artificial Intelligence (AI) in Medical by region & country, by Type, and by Application.
The Artificial Intelligence (AI) in Medical market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Artificial Intelligence (AI) in Medical.
Market Segmentation
By Company
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
Segment by Type
Machine Learning Models
Natural Language Processing
Computer Vision
Robotics
Others
Segment by Application
Medical Imaging & Diagnostics
Drug Discovery
Personalized Medicine
Healthcare Administration
Virtual Health Assistants
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia-Pacific
Europe
Germany
France
U.K.
Italy
Netherlands
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Artificial Intelligence (AI) in Medical company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Artificial Intelligence (AI) in Medical in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Artificial Intelligence (AI) in Medical in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.

Index