The global generative AI in healthcare market size was valued at $1.6 billion in 2022 and is projected to reach $30.4 billion by 2032, growing at a CAGR of 34.9% from 2023 to 2032. Generative AI has gained significant traction in the field of healthcare, revolutionizing various aspects of patient care, medical research, and administrative processes. One of its most notable applications is in medical image generation. Additionally, generative AI is being used to predict patient outcomes by generating synthetic patient data that can help researchers better understand disease progression and treatment effects while ensuring patient privacy. In the clinical domain, generative AI is assisting in medical record summarization and report generation. Natural Language Processing (NLP) models can generate concise and relevant summaries of patients' medical histories, aiding healthcare providers in making more informed decisions. Furthermore, chatbots and virtual assistants powered by generative language models offer support for patients, answering questions and providing information on various healthcare topics. Key factors driving the growth of generative AI in the healthcare market are the surge in the adoption of generative AI in healthcare in medical imaging, and the efficiency of generative AI in healthcare in clinical data management.
Generative AI has emerged as a transformative force in the field of healthcare, with its applications in medical imaging standing out as a major driver for the growth of generative AI in the healthcare market. One of the most compelling applications of generative AI in medical imaging is in the enhancement and reconstruction of medical images. Generative Adversarial Networks (GANs) and other generative models can improve the resolution and quality of images, aiding clinicians in making more accurate diagnoses. For instance, according to a 2023 report by the National Library of Medicine, generative artificial intelligence (AI) has shown great potential in enhancing medical imaging tasks such as data augmentation, image synthesis, image-to-image translation, and radiology report generation.
Furthermore, the efficiency of generative AI in healthcare in clinical data management is expected to contribute significantly to the growth of the market. Generative AI, powered by advanced natural language processing and machine learning techniques, has proven itself invaluable in transforming the way healthcare institutions handle and utilize vast volumes of clinical data. One of the most compelling aspects of generative AI is its ability to automate and streamline complex data management tasks. Generative AI can extract, organize, and categorize clinical data from a variety of sources, including electronic health records, medical imaging, and patient notes, with remarkable speed and precision. This not only reduces the burden on healthcare professionals, allowing them to focus more on patient care, but also significantly enhances the accuracy and completeness of data, which is crucial for evidence-based decision-making, research, and personalized patient treatment plans. For instance, in 2021, HCA Healthcare, Inc., one of the leading healthcare providers, and Google Cloud announced a multi-year strategic partnership. HCA Healthcare collaborated with Google Cloud on the use of generative AI to support doctors and nurses to reduce the burden of administrative tasks.
Moreover, generative AI's efficiency extends beyond data organization. It can generate comprehensive clinical reports, summaries, and predictive models by synthesizing information from disparate sources. This capability not only saves time but also aids in early disease detection, treatment optimization, and prognosis assessment. Additionally, its ability to continually learn and adapt from new data ensures that healthcare organizations stay up-to-date with the latest medical research and best practices, ultimately leading to improved patient outcomes. However, concerns related to data privacy might restrain the growth of the market.
The generative AI in healthcare market is segmented on the basis of application, end user, and region. By applications, the market is categorized into treatment, diagnosis, drug discovery, and research. As per end users, the market is categorized into hospitals & clinics, healthcare organizations, and others. Region-wise, the market is analyzed across North America (the U.S., Canada, and Mexico), Europe (Germany, France, the UK, Italy, Spain, and the rest of Europe), Asia-Pacific (Japan, China, Australia, India, South Korea, and rest of Asia-Pacific), and LAMEA (Brazil, South Africa, Saudi Arabia, and rest of LAMEA).
Major key players that operate in the global generative AI in the healthcare market are IBM Watson Health Corporation, Google LLC, Syntegra, Amazon, Open AI, NVIDIA Corporation, Oracle, Insilico Medicine, Abridge AI Inc, and Microsoft.
The market research is offered along with information related to key drivers, restraints, and opportunities.
Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders to make profit-oriented business decisions and strengthen their supplier-buyer network.
An in-depth analysis of the generative ai in healthcare market segmentation assists in determining the prevailing market opportunities.
Major countries in each region are mapped according to their revenue contribution to the global market.
Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
The report includes an analysis of the regional as well as global generative AI in healthcare market trends, key players, market segments, application areas, and market growth strategies.
Generative AI has emerged as a transformative force in the field of healthcare, with its applications in medical imaging standing out as a major driver for the growth of generative AI in the healthcare market. One of the most compelling applications of generative AI in medical imaging is in the enhancement and reconstruction of medical images. Generative Adversarial Networks (GANs) and other generative models can improve the resolution and quality of images, aiding clinicians in making more accurate diagnoses. For instance, according to a 2023 report by the National Library of Medicine, generative artificial intelligence (AI) has shown great potential in enhancing medical imaging tasks such as data augmentation, image synthesis, image-to-image translation, and radiology report generation.
Furthermore, the efficiency of generative AI in healthcare in clinical data management is expected to contribute significantly to the growth of the market. Generative AI, powered by advanced natural language processing and machine learning techniques, has proven itself invaluable in transforming the way healthcare institutions handle and utilize vast volumes of clinical data. One of the most compelling aspects of generative AI is its ability to automate and streamline complex data management tasks. Generative AI can extract, organize, and categorize clinical data from a variety of sources, including electronic health records, medical imaging, and patient notes, with remarkable speed and precision. This not only reduces the burden on healthcare professionals, allowing them to focus more on patient care, but also significantly enhances the accuracy and completeness of data, which is crucial for evidence-based decision-making, research, and personalized patient treatment plans. For instance, in 2021, HCA Healthcare, Inc., one of the leading healthcare providers, and Google Cloud announced a multi-year strategic partnership. HCA Healthcare collaborated with Google Cloud on the use of generative AI to support doctors and nurses to reduce the burden of administrative tasks.
Moreover, generative AI's efficiency extends beyond data organization. It can generate comprehensive clinical reports, summaries, and predictive models by synthesizing information from disparate sources. This capability not only saves time but also aids in early disease detection, treatment optimization, and prognosis assessment. Additionally, its ability to continually learn and adapt from new data ensures that healthcare organizations stay up-to-date with the latest medical research and best practices, ultimately leading to improved patient outcomes. However, concerns related to data privacy might restrain the growth of the market.
The generative AI in healthcare market is segmented on the basis of application, end user, and region. By applications, the market is categorized into treatment, diagnosis, drug discovery, and research. As per end users, the market is categorized into hospitals & clinics, healthcare organizations, and others. Region-wise, the market is analyzed across North America (the U.S., Canada, and Mexico), Europe (Germany, France, the UK, Italy, Spain, and the rest of Europe), Asia-Pacific (Japan, China, Australia, India, South Korea, and rest of Asia-Pacific), and LAMEA (Brazil, South Africa, Saudi Arabia, and rest of LAMEA).
Major key players that operate in the global generative AI in the healthcare market are IBM Watson Health Corporation, Google LLC, Syntegra, Amazon, Open AI, NVIDIA Corporation, Oracle, Insilico Medicine, Abridge AI Inc, and Microsoft.
Key Benefits For Stakeholders
This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the generative AI in healthcare market analysis from 2022 to 2032 to identify the prevailing generative ai in healthcare market opportunities.The market research is offered along with information related to key drivers, restraints, and opportunities.
Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders to make profit-oriented business decisions and strengthen their supplier-buyer network.
An in-depth analysis of the generative ai in healthcare market segmentation assists in determining the prevailing market opportunities.
Major countries in each region are mapped according to their revenue contribution to the global market.
Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
The report includes an analysis of the regional as well as global generative AI in healthcare market trends, key players, market segments, application areas, and market growth strategies.
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Key Market Segments
By Application
- Treatment
- Diagnosis
- Drug Discovery
- Research
By End User
- Hospitals and clinics
- Healthcare Organizations
- Others
By Region
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- Japan
- China
- Australia
- India
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Brazil
- Saudi Arabia
- South Africa
- Rest of LAMEA
- IBM Watson Health Corporation
- Amazon
- Microsoft
- Open AI Inc.
- Google LLC
- NVIDIA Corporation
- Abridge AI Inc.
- Syntegra
- InSilico Medicine
- Oracle
Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: GENERATIVE AI IN HEALTHCARE MARKET, BY APPLICATION
CHAPTER 5: GENERATIVE AI IN HEALTHCARE MARKET, BY END USER
CHAPTER 6: GENERATIVE AI IN HEALTHCARE MARKET, BY REGION
CHAPTER 7: COMPETITIVE LANDSCAPE
CHAPTER 8: COMPANY PROFILES
List of Tables
List of Figures
Companies Mentioned
- IBM Watson Health Corporation
- Amazon
- Microsoft
- Open AI Inc.
- Google LLC
- NVIDIA Corporation
- Abridge AI Inc.
- Syntegra
- InSilico Medicine
- Oracle
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | November 2023 |
| Forecast Period | 2022 - 2032 |
| Estimated Market Value ( USD | $ 1.6 billion |
| Forecasted Market Value ( USD | $ 30.4 billion |
| Compound Annual Growth Rate | 34.2% |
| Regions Covered | Global |
| No. of Companies Mentioned | 10 |
