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市場調査レポート
商品コード
1800776
ヘルスケアにおけるAIの市場レポート:提供別、技術別、用途別、エンドユーザー別、地域別、2025~2033年Artificial Intelligence in Healthcare Market Report by Offering, Technology, Application, End-User, and Region 2025-2033 |
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ヘルスケアにおけるAIの市場レポート:提供別、技術別、用途別、エンドユーザー別、地域別、2025~2033年 |
出版日: 2025年08月01日
発行: IMARC
ページ情報: 英文 140 Pages
納期: 2~3営業日
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世界のヘルスケアにおけるAIの市場規模は2024年に78億米ドルに達しました。今後、IMARC Groupは、市場は2033年までに687億米ドルに達し、2025~2033年にかけて26.04%の成長率(CAGR)を示すと予測しています。個別化された薬剤への需要の高まり、遠隔患者監視施設の人気の高まり、医療画像の分析、異常の検出、患者の転帰を効率的に予測するための機械学習(ML)技術の進歩の増加が、市場を推進している主な要因の一部です。
慢性疾患の有病率の上昇
現在、長時間の座位、身体活動の低下、不健康な食習慣など、不活発なライフスタイルに起因する慢性疾患の有病率が上昇しています。こうした生活習慣は、肥満、糖尿病、心血管疾患といった疾患の発生に寄与しています。たとえば、米国保健福祉省によると、米国では約1億2,900万人が少なくとも1つの重大な慢性疾患(心臓病、がん、糖尿病、肥満、高血圧など)を抱えています。慢性疾患の増加は入院率も押し上げ、AIを取り入れた効果的な治療法の需要も高まっています。ヘルスケアにおけるAIは、スクリーニングプロセスを改善し、様々な慢性疾患の発見を可能にしています。これらの要因は、ヘルスケアにおけるAI市場予測にさらにプラスの影響を与えます。
個別化医療への需要の高まり
個別化医療に対する需要の高まりが市場の成長を促進しています。例えば、世界の精密医療の市場規模は2023年に752億米ドルに達しました。今後、IMARC Groupは、同市場が2032年までに1,683億米ドルに達し、2024~2032年の間に9.1%の成長率(CAGR)を示すと予測しています。精密医療は、個人の遺伝的、環境的、ライフスタイル的要因に基づいて治療を調整することを目的としています。AIは膨大な量の遺伝子データを分析し、より正確で個別化された治療の推奨につながるパターンを特定することができます。これらの要因が、今後数年間のヘルスケアにおけるAI市場の成長を促進すると予想されます。
遠隔患者モニタリング
遠隔患者モニタリングは、自宅に居ながらにして健康状態を把握できるため、ヘルスケア施設に頻繁に出向く必要がなくなります。これにより、移動、待合室、その他のヘルスケア関連の不便さが制限され、患者の満足度向上につながります。特に遠隔地や十分な医療サービスを受けられない地域の患者にとっては、ヘルスケアへのアクセスが向上し、患者は場所に関係なく医療提供者とつながり、質の高いケアを受けることができます。例えば2024年7月、ジョージア州を拠点とするモノのインターネット(IoT)企業KOREとオーストラリアのmCare Digitalは、バーチャル患者モニタリングスマートウォッチ「mCareWatch 241」を発表しました。この腕時計には、緊急支援を要請できるSOSボタン、通話機能、GPS追跡、リマインダー、心拍数モニター、スピードダイヤル、転倒検知、歩数計、ジオフェンスアラーム、非移動検知、モバイルアプリとウェブダッシュボードが搭載されており、ヘルスケアにおけるAI市場の収益を押し上げています。
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.
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.
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.
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.
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.
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.
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.
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.