1. 方法論と範囲
1.1. 調査方法
1.2. 調査目的と調査範囲
2. 定義と概要
3. エグゼクティブ・サマリー
3.1. 技術別スニペット
3.2. アプリケーション別スニペット
3.3. エンドユーザー別スニペット
3.4. 地域別スニペット
4. ダイナミクス
4.1. 影響要因
4.1.1. 推進要因
4.1.1.1. 技術の進歩と高齢化人口の増加
4.1.1.2. 医療費の上昇と政府の支援
4.1.2. 阻害要因
4.1.2.1. 高齢者の限られたデジタルリテラシー
4.1.3. 機会
4.1.4. 影響分析
5. 産業分析
5.1. ポーターのファイブフォース分析
5.2. サプライチェーン分析
5.3. 価格分析
5.4. 規制分析
5.5. ロシア・ウクライナ戦争の影響分析
5.6. DMI意見
6. 技術別
6.1. はじめに
6.1.1. 市場規模分析と前年比成長率分析（%）, 技術別
6.1.2. 市場魅力度指数、技術別
6.2. 機械学習
6.2.1. はじめに
6.2.2. 市場規模分析と前年比成長率分析(%)
6.3. 自然言語処理（NLP）
6.4. ロボティクス
6.5. コンピュータビジョン
6.6. その他
7. アプリケーション別
7.1. 導入
7.1.1. 市場規模分析および前年比成長率分析（%）, アプリケーション別
7.1.2. 市場魅力度指数：用途別
7.2. 転倒検知・防止*市場
7.2.1. はじめに
7.2.2. 市場規模分析と前年比成長率分析(%)
7.3. 投薬管理
7.4. 遠隔健康モニタリング
7.5. ソーシャル・エンゲージメントとコンパニオンAI
7.6. 認知刺激と脳トレーニング
8. エンドユーザー別
8.1. はじめに
8.1.1. 市場規模分析および前年比成長率分析(%), エンドユーザー別
8.1.2. 市場魅力度指数、エンドユーザー別
8.2. 在宅介護の設定
8.2.1. はじめに
8.2.2. 市場規模分析と前年比成長率分析(%)
8.3. 生活支援施設
8.4. 老人ホームと長期ケアセンター
8.5. 病院および医療機関
9. 持続可能性分析
9.1. 環境分析
9.2. 経済分析
9.3. ガバナンス分析
10. 地域別
10.1. はじめに
10.1.1. 地域別市場規模分析および前年比成長率分析(%)
10.1.2. 市場魅力度指数、地域別
10.2. 北米
10.2.1. 序論
10.2.2. 主な地域別ダイナミクス
10.2.3. 市場規模分析および前年比成長率分析（%）, 技術別
10.2.4. 市場規模分析とYoY成長率分析（%）, アプリケーション別
10.2.5. 市場規模分析および前年比成長率分析(%)、エンドユーザー別
10.2.6. 市場規模分析および前年比成長率分析(%)、国別
10.2.6.1. 米国
10.2.6.2. カナダ
10.2.6.3. メキシコ
10.3. ヨーロッパ
10.3.1. はじめに
10.3.2. 主な地域別ダイナミクス
10.3.3. 市場規模分析および前年比成長率分析（%）, 技術別
10.3.4. 市場規模分析とYoY成長率分析（%）, アプリケーション別
10.3.5. 市場規模分析および前年比成長率分析(%)、エンドユーザー別
10.3.6. 市場規模分析および前年比成長率分析(%)、国別
10.3.6.1. ドイツ
10.3.6.2. イギリス
10.3.6.3. フランス
10.3.6.4. イタリア
10.3.6.5. スペイン
10.3.6.6. その他のヨーロッパ
10.4. 南米
10.4.1. はじめに
10.4.2. 地域別主要市場
10.4.3. 市場規模分析および前年比成長率分析（%）, 技術別
10.4.4. 市場規模分析とYoY成長率分析（%）, アプリケーション別
10.4.5. 市場規模分析および前年比成長率分析(%)、エンドユーザー別
10.4.6. 市場規模分析および前年比成長率分析(%)、国別
10.4.6.1. ブラジル
10.4.6.2. アルゼンチン
10.4.6.3. その他の南米諸国
10.5. アジア太平洋
10.5.1. 序論
10.5.2. 主な地域別ダイナミクス
10.5.3. 市場規模分析および前年比成長率分析（%）, 技術別
10.5.4. 市場規模分析とYoY成長率分析（%）, アプリケーション別
10.5.5. 市場規模分析および前年比成長率分析 (%)、エンドユーザー別
10.5.6. 市場規模分析および前年比成長率分析(%)、国別
10.5.6.1. 中国
10.5.6.2. インド
10.5.6.3. 日本
10.5.6.4. オーストラリア
10.5.6.5. その他のアジア太平洋地域
10.6. 中東・アフリカ
10.6.1. 序論
10.6.2. 主な地域別ダイナミクス
10.6.3. 市場規模分析および前年比成長率分析（%）, 技術別
10.6.4. 市場規模分析とYoY成長率分析（%）, アプリケーション別
10.6.5. 市場規模分析および前年比成長率分析（%）, エンドユーザー別
11. 競合情勢
11.1. 競争シナリオ
11.2. 市場ポジショニング／シェア分析
11.3. M&A分析
12. 企業プロフィール
12.1. IBM Corporation*
12.1.1. Company Overview
12.1.2. Type Portfolio and Description
12.1.3. Financial Overview
12.1.4. Key Developments
12.2. InteliCare
12.3. Carepredict
12.4. Intuition Robotics
12.5. Aiva Health
12.6. K4connect
12.7. UBTECH ROBOTICS CORP LTD
12.8. RapidInnovation
12.9. Koninklijke Philips N.V.
12.10. Siemens AG
リストは網羅的ではありません
13. 付録
13.1. シーメンスについて
13.2. お問い合わせ
Global AI in Elderly Care Market reached US$ 34.39 billion in 2023 and is expected to reach US$ 209.19 billion by 2031, growing with a CAGR of 25.32% during the forecast period 2024-2031.
The global market for artificial intelligence (AI) in the care of elderly citizens is growing at a remarkable growth with the introduction of new AI-powered assistive devices, the increase in life expectancy and the growing demand for effective elderly care solutions. The demand is especially high due to the racial demographic shift as the population ages and the endemic chronic diseases in the world.
Regulatory frameworks and government policies fuel the adoption of AI among the elderly. For instance, US Food and Drug Administration (FDA) has allowed quicker procedures to approve all artificial intelligence-centric medical instruments, encouraging innovation without compromising safety limits. Similarly, the risks associated with using artificial intelligence in health care in the member states are dealt with by the European Medicines Agency (EMA) which set out rules about this technology use in healthcare.
Asia-Pacific is the fastest-growing region for AI-based solutions that target elderly people’s care. The risk of posing or even higher risk of an aging population exists in nations, especially Japan, China and South Korea. Such nations support and fund the development of AI aged care technological evolution. Japan faced a fast-growing old-age population, which has prompted a lot of funding from the government for research and implementation of age-friendly AI systems.
Dynamics
Technological Advancements and Increasing Aging Population
The elderly care market is propelled by the increasing implementation of advanced technologies such as machine learning algorithms, robotic assistance and predictive analytics. These systems are essential for the management of chronic diseases and for avoiding health-related issues due to the availability of real-time data on health status. For example, devices with artificial intelligence technology can monitor a patient’s vital signs and notify the health care services if any intervention is needed to enhance the quality of care and reduce unnecessary hospitalization.
Aging Population further contributes to market expansion. According to the United Nations, the number of individuals over 65 years reach 1.5 billion globally and this will double by 2050. Such a shift in population dynamics demands effective and easily manageable elderly care options. The majority of older people wish to stay in their own homes for as long as possible, thus self-care becomes more relevant and has to be enhanced with AI-supported in-home care.
Rising Healthcare Costs and Government Support
The rising costs associated with traditional healthcare are propelling the shift toward AI-driven elderly care as a more affordable alternative. According to the World Bank, global healthcare expenditure is expected to rise by 4.6% annually over the next decade. AI-powered elderly care offers cost-saving opportunities through preventive health measures, reduced hospital admissions and efficient resource allocation. In response, several governments are implementing policies to support AI-based healthcare innovations. For example, the European Union's Horizon Europe program allocates funding for AI in healthcare projects, particularly those targeting elderly populations.
US Bureau of Labor Statistics (BLS) has also indicated that demand for healthcare workers is expected to grow by 12.6% from 2021 to 2031, with a significant portion of this increase concentrated in elderly care sectors. By incorporating AI, healthcare providers can alleviate workforce shortages and extend the reach of care professionals, enabling more effective elderly support.
Limited Digital Literacy in the Elderly Citizen
The initial costs associated with the development and deployment of advanced AI-enabled devices pose significant barriers for budget-conscious consumers and smaller healthcare facilities. These high expenses can limit accessibility to such technologies, which are designed to enhance patient care and streamline operations. The potential for data breaches raises alarms for both consumers and providers, making them hesitant to adopt these innovations.
Additionally, the limited digital literacy among the elderly population, coupled with a general resistance to new technologies, further complicates the market's growth prospects. As a result, while AI in the elderly care market holds substantial growth, these financial, privacy, educational and regulatory challenges must be addressed to foster broader acceptance and integration into everyday medical practices.
Segment Analysis
The global AI in elderly care market is segmented based on technology, application, end-user and region.
Agility in Fall Detection and Prevention Demands in the Market
The global market for fall detection and prevention solutions is gaining traction due to the increasing elderly population, high healthcare costs and growing awareness regarding fall-associated risks. Falls are dangerous for the elderly and are associated with injury and disability including internal bleeding and breaks such as femur, shoulder and cranial fractures. According to the World Health Organization (WHO), the annual global estimate of falls is 424,000 while medically attended falls have been approximated to be about 37.3 million falls.
Wearable gadgets, Environmental Sensors, AI-assisted Monitoring Systems and alert systems are all parts of fall detection and prevention system. For example, Falls are responsible for more than 3 million emergency room visits every year for people aged 65 and over according to the Centers for Disease Control and Prevention (CDC). Fall detection and prevention solutions facilitate interventions and advanced customized patient care, hence the risk of sustaining injuries from falls reduces drastically.
Geographical Penetration
High Technology Adoption and Strong Consumer Awareness in North America
North America dominates the market share for AI in elderly care services in the global market, due to the advanced healthcare system, high rate of technology acceptance and support of government policies in the region. US Census Bureau highlighted that, in 2022, 16% of the total US population was aged 65 years and above and it is expected to increase to 23% by the year 2050. These figures indicate a growing need for innovative approaches to elderly care that incorporate the application of Artificial Intelligence technologies.
The development of this market is also supported by the growing number of older people suffering from long-term chronic conditions and the increasing demand for tailored treatment. The use of artificial intelligence allows for the gathering and processing of large amounts of data from different platforms, which makes it possible to design care regimens that improve the well-being of elderly people. The role of AI in eldercare extends beyond enabling strategic health management to even mitigating concerns such as a senior citizen’s risk of social isolation or adherence to medication, which also facilitates better living conditions.
Competitive Landscape
The major global players in the market include IBM Corporation, InteliCare, CarePredict, Intuition Robotics, Aiva Health, K4connect, UBTECH ROBOTICS CORP LTD, RapidInnovation, Koninklijke Philips N.V. and Siemens AG.
Sustainability Analysis
The utilization of artificial intelligence in elderly care services is becoming more environmentally friendly as the industry develops digital healthcare solutions with a significantly lower carbon footprint. According to the Healthcare Sustainability Committee (GSHC), the use of remote patient monitoring with AI technology, achieve a 30% decrease in healthcare-associated emissions by 2030.
Apart from remote care solutions, AI companies are also engaging in energy-saving measures such as sourcing for green data centers and introducing recycling programs for medical devices. Such contributions are not only helpful for achieving environmental goals but also encourage the appropriate use of technology in medical care. With the world turning to sustainable development, a demand for aged care AI-driven solutions that offer healthier and eco-friendly solutions.
Russia-Ukraine War Impact
Geopolitical factors, especially the war between Russia and Ukraine, have resulted in considerable disturbances in the supply chains of medical and AI-related devices across the globe. Ukraine is an important hub for the global electronic components industry for medical devices and therefore, the country has experienced adverse production issues due to the war. In such circumstances, governments face the temptation to focus more on immediate problems rather than addressing the development of healthcare technologies, which could further set back the use of AI in elderly care.
This has resulted in an inability to meet the demands and delays in the supply of AI technologies within Europe, adversely affecting the regions where AI-assisted elderly care solutions were to be introduced. The ramifications of such disruptions extend into the healthcare industry where advanced technologies must be acquired at the right time to enhance services for the elderly. Additionally, since some areas under siege are progressively inclined to devote their resources to humanitarian and military activities, funding for elderly care initiatives may be adversely affected.
By Technology
● Machine Learning
● Natural Language Processing (NLP)
● Robotics
● Computer Vision
● Others
By Application
● Fall Detection and Prevention
● Medication Management
● Remote Health Monitoring
● Social Engagement and Companion AI
● Cognitive Stimulation and Brain Training
By End-User
● Home Care Settings
● Assisted Living Facilities
● Nursing Homes and Long-Term Care Centers
● Hospitals and Healthcare Institutions
By Region
● North America
o US
o Canada
o Mexico
● Europe
o Germany
o UK
o France
o Italy
o Spain
o Rest of Europe
● South America
o Brazil
o Argentina
o Rest of South America
● Asia-Pacific
o China
o India
o Japan
o Australia
o Rest of Asia-Pacific
● Middle East and Africa
Key Developments
● In July 2023, TrueCare successfully implemented an AI-driven remote patient monitoring (RPM) program to enhance blood pressure management for elderly patients with persistent hypertension, utilizing technology from Rimidi.
● In March 2023, Health Corporation announced the launch of its Care Transitions Program, designed to effectively complement patients' discharge plans, with a particular focus on reducing hospital readmissions among older adults.
● In January 2023, Baracoda, a provider of innovative IoT services, announced the launch of BHeart, an innovative health tracker with an unlimited battery. By combining artificial intelligence with cutting-edge energy-harvesting technology, BHeart offers continuous, maintenance-free monitoring of vital health metrics, enabling proactive care for the aging population.
Why Purchase the Report?
● To visualize the global AI in elderly care market segmentation based on technology, application, end-user and region.
● Identify commercial opportunities by analyzing trends and co-development.
● Excel data sheet with numerous data points at the AI in elderly care market level for all segments.
● PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
● Product mapping available as excel consisting of key products of all the major players.
The global AI in elderly care market report would provide approximately 62 tables, 57 figures and 202 pages.
Target Audience 2024
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies
1. Methodology and Scope
1.1. Research Methodology
1.2. Research Objective and Scope of the Report
2. Definition and Overview
3. Executive Summary
3.1. Snippet by Technology
3.2. Snippet by Application
3.3. Snippet by End-User
3.4. Snippet by Region
4. Dynamics
4.1. Impacting Factors
4.1.1. Drivers
4.1.1.1. Technological Advancements and Increasing Aging Population
4.1.1.2. Rising Healthcare Costs and Government Support
4.1.2. Restraints
4.1.2.1. Limited Digital Literacy in the Elderly Citizen
4.1.3. Opportunity
4.1.4. Impact Analysis
5. Industry Analysis
5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion
6. By Technology
6.1. Introduction
6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
6.1.2. Market Attractiveness Index, By Technology
6.2. Machine Learning*
6.2.1. Introduction
6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
6.3. Natural Language Processing (NLP)
6.4. Robotics
6.5. Computer Vision
6.6. Others
7. By Application
7.1. Introduction
7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
7.1.2. Market Attractiveness Index, By Application
7.2. Fall Detection and Prevention*
7.2.1. Introduction
7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Medication Management
7.4. Remote Health Monitoring
7.5. Social Engagement and Companion AI
7.6. Cognitive Stimulation and Brain Training
8. By End-User
8.1. Introduction
8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
8.1.2. Market Attractiveness Index, By End-User
8.2. Home Care Settings*
8.2.1. Introduction
8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Assisted Living Facilities
8.4. Nursing Homes and Long-Term Care Centers
8.5. Hospitals and Healthcare Institutions
9. Sustainability Analysis
9.1. Environmental Analysis
9.2. Economic Analysis
9.3. Governance Analysis
10. By Region
10.1. Introduction
10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
10.1.2. Market Attractiveness Index, By Region
10.2. North America
10.2.1. Introduction
10.2.2. Key Region-Specific Dynamics
10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
10.2.6.1. US
10.2.6.2. Canada
10.2.6.3. Mexico
10.3. Europe
10.3.1. Introduction
10.3.2. Key Region-Specific Dynamics
10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
10.3.6.1. Germany
10.3.6.2. UK
10.3.6.3. France
10.3.6.4. Italy
10.3.6.5. Spain
10.3.6.6. Rest of Europe
10.4. South America
10.4.1. Introduction
10.4.2. Key Region-Specific Dynamics
10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
10.4.6.1. Brazil
10.4.6.2. Argentina
10.4.6.3. Rest of South America
10.5. Asia-Pacific
10.5.1. Introduction
10.5.2. Key Region-Specific Dynamics
10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
10.5.6.1. China
10.5.6.2. India
10.5.6.3. Japan
10.5.6.4. Australia
10.5.6.5. Rest of Asia-Pacific
10.6. Middle East and Africa
10.6.1. Introduction
10.6.2. Key Region-Specific Dynamics
10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11. Competitive Landscape
11.1. Competitive Scenario
11.2. Market Positioning/Share Analysis
11.3. Mergers and Acquisitions Analysis
12. Company Profiles
12.1. IBM Corporation*
12.1.1. Company Overview
12.1.2. Type Portfolio and Description
12.1.3. Financial Overview
12.1.4. Key Developments
12.2. InteliCare
12.3. Carepredict
12.4. Intuition Robotics
12.5. Aiva Health
12.6. K4connect
12.7. UBTECH ROBOTICS CORP LTD
12.8. RapidInnovation
12.9. Koninklijke Philips N.V.
12.10. Siemens AG
LIST NOT EXHAUSTIVE
13. Appendix
13.1. About Us and Services
13.2. Contact Us
❖ 世界の高齢者介護におけるAI市場に関するよくある質問(FAQ) ❖
・高齢者介護におけるAIの世界市場規模は？
→DataM Intelligence社は2023年の高齢者介護におけるAIの世界市場規模を343億9000万米ドルと推定しています。
・高齢者介護におけるAIの世界市場予測は？
→DataM Intelligence社は2031年の高齢者介護におけるAIの世界市場規模を2091億9000万米ドルと予測しています。
・高齢者介護におけるAI市場の成長率は？
→DataM Intelligence社は高齢者介護におけるAIの世界市場が2024年～2031年に年平均25.3%成長すると予測しています。
・世界の高齢者介護におけるAI市場における主要企業は？
→DataM Intelligence社は「IBM Corporation, InteliCare, CarePredict, Intuition Robotics, Aiva Health, K4connect, UBTECH ROBOTICS CORP LTD, RapidInnovation, Koninklijke Philips N.V. and Siemens AG.など ...」をグローバル高齢者介護におけるAI市場の主要企業として認識しています。
※上記FAQの市場規模、市場予測、成長率、主要企業に関する情報は本レポートの概要を作成した時点での情報であり、納品レポートの情報と少し異なる場合があります。
