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The global artificial intelligence in healthcare market size reached USD 7.8 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 68.7 Billion by 2033, exhibiting a growth rate (CAGR) of 26.04% during 2025-2033. 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 in Healthcare Market Analysis:

• Major Market Drivers: 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.
• Key Market Trends: 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.
• Competitive Landscape: Some of the prominent artificial intelligence in healthcare market companies 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, and Welltok Inc., among many others.
• Geographical Trends: According to the artificial intelligence in healthcare market dynamics, North America exhibits a clear dominance in the market. North America is a hub for technological innovation, with advancements in machine learning, deep learning, and natural language processing driving the development of sophisticated AI applications in healthcare. Technologies such as AI-powered diagnostic tools, predictive analytics, and personalized medicine solutions are at the forefront.
• Challenges and Opportunities: High development costs and the rising data privacy and security issues are hampering the market's growth. However, AI has the potential to significantly improve diagnostic accuracy and treatment outcomes through advanced image analysis, predictive analytics, and personalized treatment plans.

Artificial Intelligence in Healthcare Market Trends:

Rising Prevalence of Chronic Illnesses

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. For instance, according to the U.S. Department of Health and Human Services, around 129 million people in the United States have at least one significant chronic disease (for example, heart disease, cancer, diabetes, obesity, or hypertension). 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. These factors further positively influence artificial intelligence in healthcare market forecast.

Growing Demand for Personalized Medicines

The growing demand for personalized medicine is driving the market's growth. For instance, the global precision medicine market size reached US$ 75.2 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 168.3 Billion by 2032, exhibiting a growth rate (CAGR) of 9.1% during 2024-2032. Precision medicine aims to tailor treatments based on individual genetic, environmental, and lifestyle factors. AI can analyze vast amounts of genetic data and identify patterns that lead to more accurate and personalized treatment recommendations. These factors are expected to propel artificial intelligence in healthcare market growth in the coming years.

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. For instance, in July 2024, KORE, a Georgia-based Internet of Things (IoT) firm, and Australian company mCare Digital unveiled the mCareWatch 241, a virtual patient monitoring smartwatch. The watch includes an SOS button that allows users to request emergency assistance, call capabilities, GPS tracking, reminders, a heart rate monitor, speed dialing, fall detection, a pedometer, a geo-fence alarm, non-movement detection, and a mobile app and web dashboard, and thereby boosting the artificial intelligence in healthcare market revenue.

Global Artificial Intelligence in Healthcare Industry Segmentation:

Breakup by Offering:

• Hardware
• Software
• Services

Software dominates the market

According to the artificial intelligence in healthcare market outlook, 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

Machine learning holds the largest share in the market

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

Clinical trial participant identifier holds the biggest share in the market

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.

Breakup by End-User:

• Healthcare Providers
• Pharmaceutical and Biotechnology Companies
• Patients
• Others

Pharmaceutical and biotechnology companies hold the maximum share in the market

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

North America exhibits a clear dominance, accounting for the largest artificial intelligence in healthcare market share

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. For instance, in 2018, more than half (51.8%) of adults had at least one of ten diagnosed chronic conditions (arthritis, cancer, chronic obstructive pulmonary disease, coronary heart disease, current asthma, diabetes, hepatitis, hypertension, stroke, and weak or failing kidneys), while 27.2% of U.S. adults had multiple chronic conditions. 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.

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.

Key Questions Answered in This Report

• 1.What was the size of the global artificial intelligence in healthcare market in 2024?
• 2.What is the expected growth rate of the global artificial intelligence in healthcare market during 2025-2033?
• 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 Preface

2 Scope and Methodology

• 2.1 Objectives of the Study
• 2.2 Stakeholders
• 2.3 Data Sources
  • 2.3.1 Primary Sources
  • 2.3.2 Secondary Sources
• 2.4 Market Estimation
  • 2.4.1 Bottom-Up Approach
  • 2.4.2 Top-Down Approach
• 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

• 4.1 Overview
• 4.2 Key Industry Trends

5 Global Artificial Intelligence in Healthcare Market

• 5.1 Market Overview
• 5.2 Market Performance
• 5.3 Impact of COVID-19
• 5.4 Market Forecast

6 Market Breakup by Offering

• 6.1 Hardware
  • 6.1.1 Market Trends
  • 6.1.2 Market Forecast
• 6.2 Software
  • 6.2.1 Market Trends
  • 6.2.2 Market Forecast
• 6.3 Services
  • 6.3.1 Market Trends
  • 6.3.2 Market Forecast

7 Market Breakup by Technology

• 7.1 Machine Learning
  • 7.1.1 Market Trends
  • 7.1.2 Market Forecast
• 7.2 Context Aware Computing
  • 7.2.1 Market Trends
  • 7.2.2 Market Forecast
• 7.3 Natural Language Processing
  • 7.3.1 Market Trends
  • 7.3.2 Market Forecast
• 7.4 Others
  • 7.4.1 Market Trends
  • 7.4.2 Market Forecast

8 Market Breakup by Application

• 8.1 Robot-Assisted Surgery
  • 8.1.1 Market Trends
  • 8.1.2 Market Forecast
• 8.2 Virtual Nursing Assistant
  • 8.2.1 Market Trends
  • 8.2.2 Market Forecast
• 8.3 Administrative Workflow Assistance
  • 8.3.1 Market Trends
  • 8.3.2 Market Forecast
• 8.4 Fraud Detection
  • 8.4.1 Market Trends
  • 8.4.2 Market Forecast
• 8.5 Dosage Error Reduction
  • 8.5.1 Market Trends
  • 8.5.2 Market Forecast
• 8.6 Clinical Trial Participant Identifier
  • 8.6.1 Market Trends
  • 8.6.2 Market Forecast
• 8.7 Preliminary Diagnosis
  • 8.7.1 Market Trends
  • 8.7.2 Market Forecast
• 8.8 Others
  • 8.8.1 Market Trends
  • 8.8.2 Market Forecast

9 Market Breakup by End-User

• 9.1 Healthcare Providers
  • 9.1.1 Market Trends
  • 9.1.2 Market Forecast
• 9.2 Pharmaceutical and Biotechnology Companies
  • 9.2.1 Market Trends
  • 9.2.2 Market Forecast
• 9.3 Patients
  • 9.3.1 Market Trends
  • 9.3.2 Market Forecast
• 9.4 Others
  • 9.4.1 Market Trends
  • 9.4.2 Market Forecast

10 Market Breakup by Region

• 10.1 North America
  • 10.1.1 United States
    • 10.1.1.1 Market Trends
    • 10.1.1.2 Market Forecast
  • 10.1.2 Canada
    • 10.1.2.1 Market Trends
    • 10.1.2.2 Market Forecast
• 10.2 Asia Pacific
  • 10.2.1 China
    • 10.2.1.1 Market Trends
    • 10.2.1.2 Market Forecast
  • 10.2.2 Japan
    • 10.2.2.1 Market Trends
    • 10.2.2.2 Market Forecast
  • 10.2.3 India
    • 10.2.3.1 Market Trends
    • 10.2.3.2 Market Forecast
  • 10.2.4 South Korea
    • 10.2.4.1 Market Trends
    • 10.2.4.2 Market Forecast
  • 10.2.5 Australia
    • 10.2.5.1 Market Trends
    • 10.2.5.2 Market Forecast
  • 10.2.6 Indonesia
    • 10.2.6.1 Market Trends
    • 10.2.6.2 Market Forecast
  • 10.2.7 Others
    • 10.2.7.1 Market Trends
    • 10.2.7.2 Market Forecast
• 10.3 Europe
  • 10.3.1 Germany
    • 10.3.1.1 Market Trends
    • 10.3.1.2 Market Forecast
  • 10.3.2 France
    • 10.3.2.1 Market Trends
    • 10.3.2.2 Market Forecast
  • 10.3.3 United Kingdom
    • 10.3.3.1 Market Trends
    • 10.3.3.2 Market Forecast
  • 10.3.4 Italy
    • 10.3.4.1 Market Trends
    • 10.3.4.2 Market Forecast
  • 10.3.5 Spain
    • 10.3.5.1 Market Trends
    • 10.3.5.2 Market Forecast
  • 10.3.6 Russia
    • 10.3.6.1 Market Trends
    • 10.3.6.2 Market Forecast
  • 10.3.7 Others
    • 10.3.7.1 Market Trends
    • 10.3.7.2 Market Forecast
• 10.4 Latin America
  • 10.4.1 Brazil
    • 10.4.1.1 Market Trends
    • 10.4.1.2 Market Forecast
  • 10.4.2 Mexico
    • 10.4.2.1 Market Trends
    • 10.4.2.2 Market Forecast
  • 10.4.3 Others
    • 10.4.3.1 Market Trends
    • 10.4.3.2 Market Forecast
• 10.5 Middle East and Africa
  • 10.5.1 Market Trends
  • 10.5.2 Market Breakup by Country
  • 10.5.3 Market Forecast

11 SWOT Analysis

• 11.1 Overview
• 11.2 Strengths
• 11.3 Weaknesses
• 11.4 Opportunities
• 11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

• 13.1 Overview
• 13.2 Bargaining Power of Buyers
• 13.3 Bargaining Power of Suppliers
• 13.4 Degree of Competition
• 13.5 Threat of New Entrants
• 13.6 Threat of Substitutes

14 Price Indicators

15 Competitive Landscape

• 15.1 Market Structure
• 15.2 Key Players
• 15.3 Profiles of Key Players
  • 15.3.1 Amazon Web Services Inc.
    • 15.3.1.1 Company Overview
    • 15.3.1.2 Product Portfolio
    • 15.3.1.3 Financials
  • 15.3.2 Cloudmedx Inc.
    • 15.3.2.1 Company Overview
    • 15.3.2.2 Product Portfolio
  • 15.3.3 DeepMind
    • 15.3.3.1 Company Overview
    • 15.3.3.2 Product Portfolio
    • 15.3.3.3 Financials
  • 15.3.4 Enlitic Inc.
    • 15.3.4.1 Company Overview
    • 15.3.4.2 Product Portfolio
  • 15.3.5 General Vision Inc.
    • 15.3.5.1 Company Overview
    • 15.3.5.2 Product Portfolio
  • 15.3.6 Google Inc.
    • 15.3.6.1 Company Overview
    • 15.3.6.2 Product Portfolio
    • 15.3.6.3 SWOT Analysis
  • 15.3.7 International Business Machines
    • 15.3.7.1 Company Overview
    • 15.3.7.2 Product Portfolio
    • 15.3.7.3 Financials
    • 15.3.7.4 SWOT Analysis
  • 15.3.8 iCarbonX
    • 15.3.8.1 Company Overview
    • 15.3.8.2 Product Portfolio
  • 15.3.9 Intel Corporation
    • 15.3.9.1 Company Overview
    • 15.3.9.2 Product Portfolio
    • 15.3.9.3 Financials
    • 15.3.9.4 SWOT Analysis
  • 15.3.10 Medtronic
    • 15.3.10.1 Company Overview
    • 15.3.10.2 Product Portfolio
  • 15.3.11 Micron Technology Inc.
    • 15.3.11.1 Company Overview
    • 15.3.11.2 Product Portfolio
    • 15.3.11.3 Financials
    • 15.3.11.4 SWOT Analysis
  • 15.3.12 Microsoft Corporation
    • 15.3.12.1 Company Overview
    • 15.3.12.2 Product Portfolio
    • 15.3.12.3 Financials
    • 15.3.12.4 SWOT Analysis
  • 15.3.13 Next It Corporation
    • 15.3.13.1 Company Overview
    • 15.3.13.2 Product Portfolio
  • 15.3.14 Nuance Communications Inc.
    • 15.3.14.1 Company Overview
    • 15.3.14.2 Product Portfolio
    • 15.3.14.3 Financials
    • 15.3.14.4 SWOT Analysis
  • 15.3.15 Nvidia Corporation
    • 15.3.15.1 Company Overview
    • 15.3.15.2 Product Portfolio
    • 15.3.15.3 Financials
    • 15.3.15.4 SWOT Analysis
  • 15.3.16 Siemens Healthcare
    • 15.3.16.1 Company Overview
    • 15.3.16.2 Product Portfolio
    • 15.3.16.3 Financials
    • 15.3.16.4 SWOT Analysis
  • 15.3.17 Welltok Inc.
    • 15.3.17.1 Company Overview
    • 15.3.17.2 Product Portfolio