The global artificial intelligence in healthcare market size reached US$ 6.1 Billion in 2023. Looking forward, the market is projected to reach US$ 57.2 Billion by 2032, exhibiting a growth rate (CAGR) of 28.24% during 2023-2032. The growing demand for personalized medications, rising popularity of remote patient monitoring facilities, and increasing advancements in machine learning (ML) techniques for analyzing medical images, detecting anomalies, and predicting patient outcomes efficiently are some of the major factors propelling the market.
Artificial intelligence (AI) in healthcare is the application of intelligent algorithms and computational models to analyze complex medical data, assist in diagnosis and treatment, and support healthcare decision-making processes. It encompasses various AI techniques, including machine learning (ML), natural language processing (NLP), computer vision, and expert systems.
It analyzes large volumes of patient data, including electronic health records (EHR), medical images, and genomic data, to identify patterns and make predictions. It aids in early disease detection, personalized treatment planning, and clinical decision support. Furthermore, it can assist healthcare professionals in making evidence-based decisions by providing valuable insights and recommendations based on data analysis.
At present, the increasing demand for AI in healthcare as it improves medical research and drug development processes is impelling the growth of the market. Besides this, the rising amount of data generated in the healthcare industry, including digital EHR, medical images, and genomic information, is contributing to the growth of the market. In addition, the growing advancements in ML techniques for efficiently analyzing medical images, detecting anomalies, and predicting patient outcomes are offering a favorable market outlook.
Apart from this, the increasing demand for clinical decision support systems that offer evidence-based recommendations and treatment guidelines and assist healthcare professionals in making accurate and informed decisions is supporting the growth of the market. Additionally, the rising implementation of policies and incentives by governing agencies of numerous countries to promote the adoption of AI in healthcare is bolstering the growth of the market.
The report has provided a detailed breakup and analysis of the market based on the offering. This includes hardware, software, and services. According to the report, software represented the largest segment.
Software associated with AI in healthcare comprises electronic health record (EHR) systems, imaging analysis software, clinical decision support systems (CDSS), and natural language processing (NPL) tools. They digitally store and manage patient health records and analyze and extract valuable insights from the vast amount of patient data, facilitating decision-making, personalized treatment planning, and clinical research.
They utilize computer vision and machine learning (ML) algorithms to assist radiologists in detecting abnormalities, making diagnoses, and providing quantitative measurements. They can extract relevant information, classify and categorize text, and enable voice-to-text transcription. They also enable continuous monitoring of vital signs, activity levels, and other health parameters to predict health deterioration and alert healthcare providers in real-time.
A detailed breakup and analysis of the market based on the technology have also been provided in the report. This includes machine learning, context aware computing, natural language processing, and others. According to the report, machine learning accounted for the largest market share.
Machine learning (ML) algorithms are employed to analyze patient data, such as electronic health records (EHR), medical imaging, and genetic information, to assist in disease diagnosis and prognosis. These algorithms identify patterns, classify diseases, and predict patient outcomes, aiding healthcare professionals in making accurate and timely decisions. They are capable of detecting abnormalities, segmenting organs and tumors, and assisting radiologists in interpreting images.
ML-based image analysis improves diagnostic accuracy, reduces interpretation time, and enhances early detection of diseases. ML models also predict patient outcomes by analyzing large datasets, including clinical records, genomic data, and lifestyle factors. Furthermore, they can analyze EHR to uncover valuable insights, such as disease trends, treatment patterns, and population health indicators.
A detailed breakup and analysis of the market based on the application have also been provided in the report. This includes robot-assisted surgery, virtual nursing assistant, administrative workflow assistance, fraud detection, dosage error reduction, clinical trial participant identifier, preliminary diagnosis, and others. According to the report, clinical trial participant identifier accounted for the largest market share.
A clinical trial participant identifier is assigned to individuals enrolled in a clinical trial to protect their privacy and confidentiality. It is used instead of personal identifying information (such as name or social security number) to ensure anonymity and protect the identity of participants. It helps ensure data integrity and security in clinical trials. By using identifiers instead of personal information, the potential for data errors or inconsistencies due to human error or data entry mistakes is reduced. It also helps protect sensitive information from being inadvertently disclosed or misused.
Robot-assisted surgery, also known as robotic surgery, refers to a surgical technique that utilizes robotic systems to aid surgeons in performing complex procedures with enhanced precision, dexterity, and control. It involves the use of robotic arms, specialized instruments, and a computer console operated by a surgeon.
A detailed breakup and analysis of the market based on the end-user have also been provided in the report. This includes healthcare providers, pharmaceutical and biotechnology companies, patients, and others. According to the report, pharmaceutical and biotechnology companies accounted for the largest market share.
Pharmaceutical and biotechnology companies are embracing the use of AI due to its transformative potential across various aspects of their operations. AI offers unprecedented opportunities to revolutionize drug discovery and development processes by leveraging data-driven approaches and computational modeling. Through AI algorithms, these companies can analyze vast amounts of biological and chemical data to identify potential drug targets, predict drug activity, and optimize drug design, significantly speeding up the traditionally time-consuming and expensive drug development pipeline. Additionally, AI enables precision medicine by leveraging patient data, genomics, and clinical records to develop personalized treatment approaches. AI algorithms can identify biomarkers or genetic variations associated with disease susceptibility and treatment response, allowing for targeted therapies and patient subgroup identification.
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.
North America held the biggest market share since the region has an efficient medical infrastructure. Moreover, the rising occurrence of various chronic disorders among the masses is contributing to the growth of the market.
Another contributing aspect is the growing adoption of robust technology infrastructure, including advanced computing capabilities, cloud computing resources, and data storage capacities in the healthcare sector.
Asia Pacific is estimated to expand further in this domain due to the rising construction of various hospitals, clinics, and nursing homes to provide quality healthcare services. Apart from this, increasing healthcare expenditures among the masses is propelling the market growth.
They are also developing and launching new AI-powered solutions and platforms for various healthcare domains, including diagnostic imaging, clinical decision support, remote patient monitoring, genomics, and drug discovery. Leading companies are focusing on strategic partnerships and collaborations to enhance their market reach, access new customer segments, and leverage complementary technologies.
The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided.
In March 2023, Nvidia Corporation announced the launch of an expanded set of generative AI cloud services for customizing AI foundation models to accelerate the production of novel proteins and therapeutics.
In November 2022, Nuance Communications Inc. announced a partnership with Nvidia Corporation for bringing medical imaging AI models directly into clinical settings and improving patient care solutions.
2. What is the expected growth rate of the global artificial intelligence in healthcare market during 2024-2032?
3. What has been the impact of COVID-19 on the global artificial intelligence in healthcare market?
4. What are the key factors driving the global artificial intelligence in healthcare market?
5. What is the breakup of the global artificial intelligence in healthcare market based on the offering?
6. What is the breakup of the global artificial intelligence in healthcare market based on the technology?
7. What is the breakup of the global artificial intelligence in healthcare market based on the application?
8. What is the breakup of the global artificial intelligence in healthcare market based on the end-user?
9. What are the key regions in the global artificial intelligence in healthcare market?
10. Who are the key players/companies in the global artificial intelligence in healthcare market?
Artificial intelligence (AI) in healthcare is the application of intelligent algorithms and computational models to analyze complex medical data, assist in diagnosis and treatment, and support healthcare decision-making processes. It encompasses various AI techniques, including machine learning (ML), natural language processing (NLP), computer vision, and expert systems.
It analyzes large volumes of patient data, including electronic health records (EHR), medical images, and genomic data, to identify patterns and make predictions. It aids in early disease detection, personalized treatment planning, and clinical decision support. Furthermore, it can assist healthcare professionals in making evidence-based decisions by providing valuable insights and recommendations based on data analysis.
At present, the increasing demand for AI in healthcare as it improves medical research and drug development processes is impelling the growth of the market. Besides this, the rising amount of data generated in the healthcare industry, including digital EHR, medical images, and genomic information, is contributing to the growth of the market. In addition, the growing advancements in ML techniques for efficiently analyzing medical images, detecting anomalies, and predicting patient outcomes are offering a favorable market outlook.
Apart from this, the increasing demand for clinical decision support systems that offer evidence-based recommendations and treatment guidelines and assist healthcare professionals in making accurate and informed decisions is supporting the growth of the market. Additionally, the rising implementation of policies and incentives by governing agencies of numerous countries to promote the adoption of AI in healthcare is bolstering the growth of the market.
Artificial Intelligence in Healthcare Market Trends/Drivers
Rising demand for personalized medications
Personalized medications are tailored to the unique characteristics of individuals, such as genetics, lifestyle, and medical history. By considering these factors, personalized medications possess the potential to be more effective in treating specific conditions compared to traditional one-size-fits-all approaches. Besides this, personalized medications aim to deliver targeted treatments based on the specific characteristics of each patient, allowing for more accurate diagnoses and tailored therapies. In addition, the integration of AI in the development of personalized medication is improving the accuracy of the process. It is also helping in identifying specific biomarkers that aim to deliver targeted treatments based on the specific characteristics of each patient, allowing for more accurate diagnoses and tailored therapies.Increasing popularity of remote patient monitoring
Remote patient monitoring enables individuals to track their health from the comfort of their own homes, eliminating the need for frequent trips to healthcare facilities. This limits the inconvenience of travel, waiting rooms, and other healthcare-related inconveniences, leading to improved patient satisfaction. It enhances healthcare accessibility, particularly for those in remote or underserved areas, allowing patients to connect with healthcare providers and receive high-quality care regardless of their location. Real-time monitoring by employing medical devices integrated with artificial intelligence (AI) enables healthcare providers to promptly detect any abnormalities or deviations in patient health. AI in healthcare plays a crucial role in remote patient monitoring by enhancing the effectiveness and efficiency of the process.Increasing occurrence of chronic disorders among the masses
Presently, there is a rise in the prevalence of chronic illnesses caused by inactive lifestyles, such as prolonged sitting, decreased physical activity, and unhealthy eating habits. These lifestyle factors contribute to the emergence of conditions like obesity, diabetes, and cardiovascular diseases. In addition, poor dietary choices involving excessive consumption of processed foods, sugary drinks, and foods high in saturated fats also contribute to the development of chronic ailments. The increase in chronic diseases is also driving hospitalization rates and the demand for effective treatment methods by incorporating AI. AI in healthcare is improving the screening process and detection of various chronic disorders. It is also assisting healthcare professionals to make the correct decision and accurate diagnoses.Artificial Intelligence in Healthcare Industry Segmentation
This report provides an analysis of the key trends in each segment of the global artificial intelligence in healthcare market report, along with forecasts at the global, regional and country levels from 2024-2032. The report has categorized the market based on offering, technology, application, and end-user.Breakup by Offering:
- Hardware
- Software
- Services
The report has provided a detailed breakup and analysis of the market based on the offering. This includes hardware, software, and services. According to the report, software represented the largest segment.
Software associated with AI in healthcare comprises electronic health record (EHR) systems, imaging analysis software, clinical decision support systems (CDSS), and natural language processing (NPL) tools. They digitally store and manage patient health records and analyze and extract valuable insights from the vast amount of patient data, facilitating decision-making, personalized treatment planning, and clinical research.
They utilize computer vision and machine learning (ML) algorithms to assist radiologists in detecting abnormalities, making diagnoses, and providing quantitative measurements. They can extract relevant information, classify and categorize text, and enable voice-to-text transcription. They also enable continuous monitoring of vital signs, activity levels, and other health parameters to predict health deterioration and alert healthcare providers in real-time.
Breakup by Technology:
- Machine Learning
- Context Aware Computing
- Natural Language Processing
- Others
A detailed breakup and analysis of the market based on the technology have also been provided in the report. This includes machine learning, context aware computing, natural language processing, and others. According to the report, machine learning accounted for the largest market share.
Machine learning (ML) algorithms are employed to analyze patient data, such as electronic health records (EHR), medical imaging, and genetic information, to assist in disease diagnosis and prognosis. These algorithms identify patterns, classify diseases, and predict patient outcomes, aiding healthcare professionals in making accurate and timely decisions. They are capable of detecting abnormalities, segmenting organs and tumors, and assisting radiologists in interpreting images.
ML-based image analysis improves diagnostic accuracy, reduces interpretation time, and enhances early detection of diseases. ML models also predict patient outcomes by analyzing large datasets, including clinical records, genomic data, and lifestyle factors. Furthermore, they can analyze EHR to uncover valuable insights, such as disease trends, treatment patterns, and population health indicators.
Breakup by Application:
- Robot-Assisted Surgery
- Virtual Nursing Assistant
- Administrative Workflow Assistance
- Fraud Detection
- Dosage Error Reduction
- Clinical Trial Participant Identifier
- Preliminary Diagnosis
- Others
A detailed breakup and analysis of the market based on the application have also been provided in the report. This includes robot-assisted surgery, virtual nursing assistant, administrative workflow assistance, fraud detection, dosage error reduction, clinical trial participant identifier, preliminary diagnosis, and others. According to the report, clinical trial participant identifier accounted for the largest market share.
A clinical trial participant identifier is assigned to individuals enrolled in a clinical trial to protect their privacy and confidentiality. It is used instead of personal identifying information (such as name or social security number) to ensure anonymity and protect the identity of participants. It helps ensure data integrity and security in clinical trials. By using identifiers instead of personal information, the potential for data errors or inconsistencies due to human error or data entry mistakes is reduced. It also helps protect sensitive information from being inadvertently disclosed or misused.
Robot-assisted surgery, also known as robotic surgery, refers to a surgical technique that utilizes robotic systems to aid surgeons in performing complex procedures with enhanced precision, dexterity, and control. It involves the use of robotic arms, specialized instruments, and a computer console operated by a surgeon.
Breakup by End-User:
- Healthcare Providers
- Pharmaceutical and Biotechnology Companies
- Patients
- Others
A detailed breakup and analysis of the market based on the end-user have also been provided in the report. This includes healthcare providers, pharmaceutical and biotechnology companies, patients, and others. According to the report, pharmaceutical and biotechnology companies accounted for the largest market share.
Pharmaceutical and biotechnology companies are embracing the use of AI due to its transformative potential across various aspects of their operations. AI offers unprecedented opportunities to revolutionize drug discovery and development processes by leveraging data-driven approaches and computational modeling. Through AI algorithms, these companies can analyze vast amounts of biological and chemical data to identify potential drug targets, predict drug activity, and optimize drug design, significantly speeding up the traditionally time-consuming and expensive drug development pipeline. Additionally, AI enables precision medicine by leveraging patient data, genomics, and clinical records to develop personalized treatment approaches. AI algorithms can identify biomarkers or genetic variations associated with disease susceptibility and treatment response, allowing for targeted therapies and patient subgroup identification.
Breakup by Region:
- North America
- United States
- Canada
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Others
- Europe
- Germany
- France
- United Kingdom
- Italy
- Spain
- Russia
- Others
- Latin America
- Brazil
- Mexico
- Others
- Middle East and Africa
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.
North America held the biggest market share since the region has an efficient medical infrastructure. Moreover, the rising occurrence of various chronic disorders among the masses is contributing to the growth of the market.
Another contributing aspect is the growing adoption of robust technology infrastructure, including advanced computing capabilities, cloud computing resources, and data storage capacities in the healthcare sector.
Asia Pacific is estimated to expand further in this domain due to the rising construction of various hospitals, clinics, and nursing homes to provide quality healthcare services. Apart from this, increasing healthcare expenditures among the masses is propelling the market growth.
Competitive Landscape
Key market players are investing in research operations to improve their AI capabilities. They are also allocating significant resources to develop new algorithms, models, and platforms that can enhance the accuracy, efficiency, and effectiveness of AI applications in healthcare. Top companies are expanding and diversifying their product portfolios to meet evolving market needs.They are also developing and launching new AI-powered solutions and platforms for various healthcare domains, including diagnostic imaging, clinical decision support, remote patient monitoring, genomics, and drug discovery. Leading companies are focusing on strategic partnerships and collaborations to enhance their market reach, access new customer segments, and leverage complementary technologies.
The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided.
Some of the key players in the market include:
- Amazon Web Services Inc.
- Cloudmedx Inc.
- DeepMind
- Enlitic Inc.
- General Vision Inc.
- Google Inc.
- International Business Machines
- iCarbonX
- Intel Corporation
- Medtronic
- Micron Technology Inc.
- Microsoft Corporation
- Next It Corporation
- Nuance Communications Inc.
- Nvidia Corporation
- Siemens Healthcare
- Welltok Inc.
Recent Developments
In March 2023, Medtronic plc announced a strategic collaboration with Cosmo Pharmaceutical and Nvidia Corporation to deliver the GI Genius™ intelligent endoscopy module - the first FDA-cleared, AI-assisted colonoscopy tool to help physicians detect polyps that can lead to colorectal cancer.In March 2023, Nvidia Corporation announced the launch of an expanded set of generative AI cloud services for customizing AI foundation models to accelerate the production of novel proteins and therapeutics.
In November 2022, Nuance Communications Inc. announced a partnership with Nvidia Corporation for bringing medical imaging AI models directly into clinical settings and improving patient care solutions.
Key Questions Answered in This Report
1. What was the size of the global artificial intelligence in healthcare market in 2023?2. What is the expected growth rate of the global artificial intelligence in healthcare market during 2024-2032?
3. What has been the impact of COVID-19 on the global artificial intelligence in healthcare market?
4. What are the key factors driving the global artificial intelligence in healthcare market?
5. What is the breakup of the global artificial intelligence in healthcare market based on the offering?
6. What is the breakup of the global artificial intelligence in healthcare market based on the technology?
7. What is the breakup of the global artificial intelligence in healthcare market based on the application?
8. What is the breakup of the global artificial intelligence in healthcare market based on the end-user?
9. What are the key regions in the global artificial intelligence in healthcare market?
10. Who are the key players/companies in the global artificial intelligence in healthcare market?
Table of Contents
1 Preface3 Executive Summary12 Value Chain Analysis14 Price Indicators
2 Scope and Methodology
4 Introduction
5 Global Artificial Intelligence in Healthcare Market
6 Market Breakup by Offering
7 Market Breakup by Technology
8 Market Breakup by Application
9 Market Breakup by End-User
10 Market Breakup by Region
11 SWOT Analysis
13 Porters Five Forces Analysis
15 Competitive Landscape
List of Figures
List of Tables
Companies Mentioned
- Amazon Web Services Inc.
- Cloudmedx Inc.
- DeepMind
- Enlitic Inc.
- General Vision Inc.
- Google Inc.
- International Business Machines
- iCarbonX
- Intel Corporation
- Medtronic
- Micron Technology Inc.
- Microsoft Corporation
- Next It Corporation
- Nuance Communications Inc.
- Nvidia Corporation
- Siemens Healthcare
- Welltok Inc. etc.
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 145 |
| Published | April 2024 |
| Forecast Period | 2023 - 2032 |
| Estimated Market Value ( USD | $ 6.1 Billion |
| Forecasted Market Value ( USD | $ 57.2 Billion |
| Compound Annual Growth Rate | 28.2% |
| Regions Covered | Global |
| No. of Companies Mentioned | 17 |
