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헬스케어AI 시장 보고서 : 제공별, 기술별, 용도별, 최종사용자별, 지역별(2025-2033년)
Artificial Intelligence in Healthcare Market Report by Offering, Technology, Application, End-User, and Region 2025-2033
상품코드 : 1800776
리서치사 : IMARC
발행일 : 2025년 08월
페이지 정보 : 영문 140 Pages
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한글목차

세계 헬스케어 분야 AI 시장 규모는 2024년 78억 달러에 달헀습니다. IMARC Group은 2033년까지 시장이 687억 달러에 달하고, 2025-2033년까지 26.04%의 연평균 성장률(CAGR)을 보일 것으로 예측했습니다. 맞춤형 약물에 대한 수요 증가, 원격 환자 모니터링 시설의 인기 증가, 의료 영상 분석, 이상 징후 감지, 환자 결과를 효율적으로 예측하기 위한 머신러닝(ML) 기술의 발전은 시장을 이끄는 주요 요인 중 일부입니다.

헬스케어 분야 AI 시장 분석

헬스케어 분야 AI 시장 동향

만성질환 유병률 증가

현재 장시간 앉아있는 자세, 신체 활동 감소, 건강에 해로운 식습관 등 비활동적인 생활습관으로 인한 만성질환의 유병률이 증가하고 있습니다. 이러한 생활습관은 비만, 당뇨병, 심혈관 질환과 같은 질병의 발생에 기여하고 있습니다. 예를 들어, 미국 보건복지부에 따르면 미국에서는 약 1억 2,900만 명이 적어도 한 가지 이상의 심각한 만성질환(심장병, 암, 당뇨병, 비만, 고혈압 등)을 앓고 있다고 합니다. 만성질환 증가로 입원율도 높아지면서 AI를 활용한 효과적인 치료법에 대한 수요도 증가하고 있습니다. 헬스케어 분야의 AI는 스크리닝 프로세스를 개선하고 다양한 만성질환을 발견할 수 있도록 돕고 있습니다. 이러한 요인들은 헬스케어 분야의 AI 시장 전망에 더욱 긍정적인 영향을 미칠 것입니다.

개인 맞춤형 의료에 대한 수요 증가

개인 맞춤형 의료에 대한 수요 증가가 시장 성장을 가속하고 있습니다. 예를 들어, 2023년 세계 정밀의료 시장 규모는 752억 달러에 달했습니다. IMARC Group은 이 시장이 2032년까지 1,683억 달러에 달하고, 2024-2032년 사이 9.1%의 연평균 성장률(CAGR)을 보일 것으로 예측하고 있습니다. 정밀의료는 개인의 유전적, 환경적, 생활습관적 요인에 따라 치료를 조정하는 것을 목표로 합니다. AI는 방대한 양의 유전자 데이터를 분석하여 보다 정확하고 맞춤화된 치료법을 추천할 수 있는 패턴을 식별할 수 있습니다. 이러한 요인들은 향후 몇 년 동안 헬스케어 분야의 AI 시장 성장을 가속할 것으로 예측됩니다.

원격 환자 모니터링

원격 환자 모니터링은 집에서도 건강 상태를 파악할 수 있기 때문에 의료시설에 자주 갈 필요가 없어집니다. 이를 통해 이동, 대기실, 기타 의료 관련 불편함이 제한되어 환자의 만족도를 높일 수 있습니다. 특히 원격지나 의료 서비스가 부족한 지역의 환자들에게 의료 접근성이 향상되고, 환자는 장소에 구애받지 않고 의료 제공업체와 연결되어 양질의 치료를 받을 수 있게 됩니다. 예를 들어, 2024년 7월, 조지아에 본사를 둔 사물인터넷(IoT) 기업 KORE와 호주의 mCare Digital은 가상 환자 모니터링 스마트워치 'mCareWatch 241'을 발표했습니다. 이 시계는 SOS 버튼, 통화 기능, GPS 추적, 알림, 심박수 모니터, 단축 다이얼, 낙상 감지, 만보계, 지오펜스 알람, 비동작 감지, 모바일 앱 및 웹 대시보드 등 다양한 기능을 탑재하고 있어 헬스케어 분야의 AI 시장 수익을 헬스케어 분야의 AI 시장 매출을 끌어올리고 있습니다.

목차

제1장 서문

제2장 조사 범위와 조사 방법

제3장 주요 요약

제4장 서론

제5장 세계의 헬스케어 AI 시장

제6장 시장 분석 : 제공별

제7장 시장 분석 : 기술별

제8장 시장 분석 : 용도별

제9장 시장 분석 : 최종사용자별

제10장 시장 분석 : 지역별

제11장 SWOT 분석

제12장 밸류체인 분석

제13장 Porter의 Five Forces 분석

제14장 가격 지표

제15장 경쟁 구도

LSH
영문 목차

영문목차

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:

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:

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 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:

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:

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 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:

Key Questions Answered in This Report

Table of Contents

1 Preface

2 Scope and Methodology

3 Executive Summary

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

12 Value Chain Analysis

13 Porters Five Forces Analysis

14 Price Indicators

15 Competitive Landscape

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