AI-powered voice assistants for older adults: a literature review of insights, research practices, and future directions

Abstract

As the global population of older adults grows, AI-powered Voice Assistants (VAs) are explored as tools to mitigate loneliness, social isolation, and cognitive decline. By enabling intuitive, hands-free interaction, VAs provide a means to enhance independence, emotional well-being, and daily functioning for older adults. This paper presents a systematic review on older adults’ interactions with VAs, analysing 48 studies, which is more than double the scope of prior reviews. Studies were selected from an initial pool of 109 publications across three major Human-Computer Interaction (HCI) databases: Scopus, PubMed, and the ACM Digital Library. Through thematic analysis of research questions addressed in the selected studies, six key research themes were identified: (1) usage patterns and interaction behaviours, (2) adoption barriers and learnability challenges, (3) user experience and satisfaction, (4) cognitive and emotional impacts, (5) design considerations for older adults, and (6) future directions. A major finding is the VAs potential role in offering emotional companionship, particularly for socially isolated individuals. However, findings also suggested that technological illiteracy, trust concerns, and usability challenges hinder VAs’ adoption. This review highlights several important gaps in the existing literature. There is a lack of longitudinal research, and limited understanding of how these systems are used in real-world settings compared to controlled environments. Many studies also fail to report participants’ levels of technological experience and rely on samples that are not fully representative of the broader older adult population. Taken together, these limitations suggest that current research may not fully capture long-term use, contextual variability, or the diversity of older adults. In response, this paper outlines a set of evidence-based recommendations for future research and design. It emphasises the need to account for novelty effects in short-term studies and to adopt more ecologically valid approaches, such as in-home or longer-term deployments. It also highlights the importance of minimising artificial constraints that may influence user behaviour, and of systematically documenting user–device interactions alongside participants’ digital literacy. These steps can support more rigorous and representative evaluation practices, contributing to the development of voice assistant technologies that are better aligned with real-world use and more accessible, ethical, and effective for older adults.