AI in Aging and Elderly Care Market Size was valued at USD 47.4 Bn in 2024 and is predicted to reach USD 322.4 Bn by 2034 at a 21.2% CAGR during the forecast period for 2025-2034.
The main goal of the book Artificial Intelligence in Aging and Elderly Care is to use state-of-the-art AI technologies to address the issues brought on by an aging population. These creative solutions support the growing number of older adults due to increased life expectancy and enable remote monitoring and early health issue detection for caregivers and healthcare providers. AI-driven solutions encourage healthy aging and active lifestyles among the aged population by providing them with smart home appliances, virtual health assistants, and robotic companions. These innovations make society more inclusive and age-friendly.
The COVID-19 epidemic has significantly impacted artificial intelligence in the aging and elder care sector. The increased susceptibility of older persons to the virus has led to an increased emphasis on using AI-driven solutions to guarantee their security and welfare—distant medical. During the pandemic, telemedicine, virtual health aids, and monitoring have become more popular, enabling medical professionals to give care with less direct patient interaction. AI-driven solutions have also been crucial in detecting early COVID-19 signs in older people, allowing for prompt therapies and lowering the risk of transmission in care settings. But the pandemic has also brought attention to issues with older persons' access to technology and data privacy, which calls for more work to solve these issues.
The AI in the aging and elderly care market is segmented based on type, application, end-user, and technology. The market is segmented based on type, such as natural language processing (NLP) systems, robotics and robotic assistance, smart home devices and IoT solutions, machine learning and predictive analytics and virtual health assistants. Based on the application, the market is segmented into fall detection and prevention, medication management, remote health monitoring, social engagement companion AI, cognitive stimulation and brain training. The market is segmented based on end-users into assisted living facilities, home care settings, nursing homes, long-term care centres, hospitals, and healthcare institutions. The market is segmented based on technology such as wearable devices, smart home systems, mobile apps, cloud computing, and the Internet of Things (IoT).
Integrating the Internet of Things (IoT) and connected devices is a major growth element in the AI-powered solutions for the elder care market. IoT and connected devices in the senior care industry have several uses and advantages. Real-time data gathering and processing is made possible by wearable sensors, smart home automation systems, and remote monitoring equipment. By integrating these devices, caregivers and medical professionals may keep an eye on vital signs, activity levels, medication compliance, and fall or emergency detection from a distance. The intelligent amalgamation of diverse gadgets and AI-driven systems facilitates proactive and customized care, guaranteeing security, welfare, and an enhanced standard of living for senior citizens. The application of IoT and linked devices in elder care enhances the capacity for remote monitoring and enables early health diagnosis.
The industry offers a variety of solutions, such as natural language processing (NLP) systems, which provide easy engagement and communication with senior citizens. IoT solutions and smart home devices enable networked settings for remote safety monitoring, while robotics and robotic assistance are essential for giving companionship and physical support. Personalized treatment plans and early health issue diagnosis are primarily made possible by machine learning and predictive analytics. Furthermore, virtual health assistants provide medication management assistance, cognitive stimulation, and virtual companionship.
In the market for AI-powered senior care solutions, North America is expected to register the highest market share. Other elements add to the region's importance. The need for innovative aged care solutions is fueled by North America's vast aging population and highly developed healthcare system. Significant R&D activity, government financing, and collaboration between IT companies and healthcare institutions all benefit the area. Additionally, the wearables, AI-powered platforms, and remote monitoring systems markets are well-established in North America, which facilitates the integration of AI technologies into elderly care. It is important to remember, though, that the market for AI-powered solutions for senior care is expanding quickly.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 47.4 Bn |
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Revenue Forecast In 2034 |
USD 322.4 Bn |
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Growth Rate CAGR |
CAGR of 21.2% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type, By Application, By Technology, By End-user |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
IBM Corporation, Intel Corporation, Google LLC, Microsoft Corporation, Amazon Web Services, Inc., NVIDIA Corporation, Siemens Healthineers AG, Oracle Corporation, General Electric Company, Medtronic PLC, Koninklijke Philips N.V., Samsung Electronics Co., Ltd., Cognivue Corporation, AARP Services, Inc., CarePredict, Inc., Sensely, Inc., Ayasdi AI, Inc., Somatix Inc., Orbita, Inc., Suki.AI, Inc., Reemo Health, Inc., True Link Financial, Inc., Eversense Corporation, Canary Health Technologies, Inc., AiCure LLC, and others. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Artificial Intelligence in Aging and Elderly Care Market Snapshot
Chapter 4. Global Artificial Intelligence in Aging and Elderly Care Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Type:
5.2.1. Natural Language Processing (NLP) Systems
5.2.2. Robotics and Robotic Assistance
5.2.3. Smart Home Devices and IoT Solutions
5.2.4. Machine Learning and Predictive Analytics
5.2.5. Virtual Health Assistants
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Application:
6.2.1. Fall Detection and Prevention
6.2.2. Medication Management
6.2.3. Remote Health Monitoring
6.2.4. Social Engagement and Companion AI
6.2.5. Cognitive Stimulation and Brain Training
Chapter 7. Market Segmentation 3: by End-User Estimates & Trend Analysis
7.1. by End-User & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End-User:
7.2.1. Home Care Settings
7.2.2. Assisted Living Facilities
7.2.3. Nursing Homes and Long-Term Care Centers
7.2.4. Hospitals and Healthcare Institutions
Chapter 8. Artificial Intelligence in Aging and Elderly Care Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.1.2. North America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.1.3. North America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
8.1.4. North America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.2. Europe
8.2.1. Europe Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.2.2. Europe Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.2.3. Europe Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
8.2.4. Europe Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.3. Asia Pacific
8.3.1. Asia Pacific Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.3.2. Asia Pacific Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.3.3. Asia-Pacific Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
8.3.4. Asia Pacific Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.4. Latin America
8.4.1. Latin America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.4.2. Latin America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.4.3. Latin America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
8.4.4. Latin America Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.5. Middle East & Africa
8.5.1. Middle East & Africa Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.5.2. Middle East & Africa Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.5.3. Middle East & Africa Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
8.5.4. Middle East & Africa Artificial Intelligence in Aging and Elderly Care Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. IBM Corporation
9.2.2. Google LLC
9.2.3. Microsoft Corporation
9.2.4. Intel Corporation
9.2.5. NVIDIA Corporation
9.2.6. Siemens Healthineers
9.2.7. CarePredict
9.2.8. Somatix
9.2.9. AiCure
9.2.10. Zebra Medical Vision
9.2.11. GrandCare Systems
9.2.12. Other Prominent Players
AI in the Aging and Elderly Care Market- By Type
AI in the Aging and Elderly Care Market- By Application
AI in the Aging and Elderly Care Market- By End-User
AI in the Aging and Elderly Care Market- By Technology
AI in the Aging and Elderly Care Market- By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
