헬스케어용 인공지능 시장 보고서 : 오퍼링, 기술, 용도, 최종사용자, 지역별(2024-2032년)

The global artificial intelligence in healthcare market size reached US$ 6.1 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 57.2 Billion by 2032, exhibiting a growth rate (CAGR) of 27.4% during 2024-2032. 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.

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:

IMARC Group 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. Our report has categorized the market based on offering, technology, application, and end-user.

Breakup by Offering:

Hardware

Software

Services

Software dominates 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.

Breakup by Technology:

Machine Learning

Context Aware Computing

Natural Language Processing

Others

Machine learning holds the largest share in the market

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

Clinical trial participant identifier holds the biggest share in the market

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

Pharmaceutical and biotechnology companies hold the maximum share in the market

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

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.

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(TM) 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 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