Artificial Intelligence and Aging in Place: A Scoping Review of Current Applications and Future Directions

Abstract

Background and objectives: As the global population continues to age, aging in place (AIP) has emerged as an essential strategy to help older adults live safely and independently within their communities. Although artificial intelligence (AI) holds promise for supporting AIP, particularly in clinical settings, limited research has focused on its application in nonclinical dimensions of AIP. This scoping review aims to explore the current landscape of AI in AIP research, focusing on its potential to address both the health and social aspects of aging outside of clinical settings.

Research design and methods: Using a scoping review framework, the study analyzed 32 empirical studies sourced from 4 electronic databases: PsycINFO, CINAHL, MEDLINE, and PubMed. The focus was on identifying the themes related to AI in AIP-related studies.

Results: The review identified 5 key themes: health and well-being, social inclusion and connectedness, successful and active aging, healthcare and end-of-life care, and public health and community strategies. many studies did not fully integrate broader environmental and contextual factors, which are critical for creating comprehensive AIP solutions. Few studies employed theoretical frameworks, limiting the ability to analyze how social, physical, and service-related factors influence AIP outcomes. Ethical issues such as fairness and AI bias were also underexplored.

Discussion and implications: The review emphasizes the need for future research to validate AI models across diverse populations and to better integrate environmental and social factors. This would ensure more equitable and effective AI-supported interventions and policies that enhance AIP for diverse aging populations.

Keywords: Aging in place; Artificial intelligence; Machine learning.