Article

Redefining Elderly Care with Agentic AI: Challenges and Opportunities

Details

Citation

Khalil RA, Ahmad K & Ali H (2026) Redefining Elderly Care with Agentic AI: Challenges and Opportunities. Ali H (Researcher) IEEE Open Journal of the Computer Society, pp. 1-18. https://ieeexplore.ieee.org/document/11328752; https://doi.org/10.1109/ojcs.2026.3650842

Abstract
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.

Keywords
Aging, Agentic AI, Artificial Intelligence, Elderly Care, Mental health, Monitoring

Journal
IEEE Open Journal of the Computer Society

StatusPublished
Publication date31/12/2026
Publication date online31/01/2026
Date accepted by journal18/12/2025
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publisher URLhttps://ieeexplore.ieee.org/document/11328752
ISSN2644-1268
eISSN2644-1268

People (1)

Dr Hazrat Ali

Dr Hazrat Ali

Lecturer in A.I/Data Science, Computing Science