Redefining Elderly Care With Agentic AI: Challenges and Opportunities
Переосмысление ухода за пожилыми людьми с помощью агентного искусственного интеллекта: проблемы и возможности
2026-01-01
SCID: 54.1/yqqf5bms
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Agentic AILarge Language Modelsautonomous decision-makingelderly careethical safeguards
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Abstract (AI)
The global ageing population necessitates new and emerging strategies for caring for older adults. In this article, we explore the potential for transformation in elderly care through Agentic Artificial Intelligence (AI), powered by Large Language Models (LLMs). We discuss how Agentic AI facilitates proactive, autonomous decision-making in elderly care. Personalized tracking of health, cognitive care, and environmental management, all aimed at enhancing independence and high-level living for older adults, represents important areas of application. With the potential to significantly transform elderly care, Agentic AI also raises profound concerns about data privacy and security, decision independence, and access. We share key insights to emphasize the need for ethical safeguards, privacy protections, and transparent decision-making. Our goal in this article is to provide a balanced discussion of both the potential and the challenges of Agentic AI, and to offer insights into its responsible use in elderly care, aligning it with the requirements and vulnerabilities specific to the elderly. Finally, we identify the priorities for the academic research communities to achieve human-centred advancements and integration of Agentic AI in elderly care. To the best of our knowledge, this is one of the first comprehensive studies explicitly focused on LLM-based Agentic AI for elderly care. Hence, we address the literature gap by analyzing the unique capabilities, applications, and limitations of LLM-based Agentic AI in elderly care.
Key Findings
1
Deployment raises major concerns about data privacy and security, preservation of decision-making independence, and equitable access.
2
Key application areas include personalized health tracking, cognitive care, and environmental management to support independence and quality of life.
3
LLM-based Agentic AI could transform elderly care through proactive, autonomous decision-making tailored to older adults’ needs.
4
Responsible integration requires ethical safeguards, strong privacy protections, and transparent decision-making aligned with older adults’ vulnerabilities.
5
The article identifies research priorities for human-centered adoption and addresses a literature gap as one of the first comprehensive studies of LLM-based Agentic AI in elderly care.
Research Object
LLM-based Agentic AI in elderly care for older adults
Research Subject
Its proactive and autonomous decision-making, personalized health and cognitive care, environmental management, and associated ethical, privacy, security, independence, and access challenges
Publication Details
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2026-01-01
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