Paper Type
Complete
Paper Number
PACIS2026-1157
Description
Artificial intelligence (AI)-based devices are increasingly embedded in everyday technologies used by older adults, yet research on AI adoption has largely focused on organizational or domain-specific contexts, leaving everyday use among older populations underexplored. Drawing on Socioemotional Selectivity Theory and digital divide research, this study investigates which socioemotional factors determine older adults’ intention to use AI-based devices. Using survey data from 303 older adults, we analyze how factors as enjoyment, perceived social isolation, or privacy concerns influence performance expectancy and the usage intention. The results show that socioemotional factors act as antecedents of performance expectancy and significantly influence intention to use AI-based devices. By integrating a lifespan perspective with established adoption constructs, this study contributes to IS research by explaining how socioemotional priorities shape technology acceptance in later life and by highlighting implications for the deployment strategy of AI-based technologies to support social connectedness and transparent data practices.
Recommended Citation
Kniepkamp, Sophie; Wortmann, Theresa; and Kroenung, Julia, "Understanding Older Adults’ Intention to Use AI-based Devices: A Socioemotional Selectivity Perspective" (2026). PACIS 2026 Proceedings. 1.
https://aisel.aisnet.org/pacis2026/ai_ethic/ai_ethic/1
Understanding Older Adults’ Intention to Use AI-based Devices: A Socioemotional Selectivity Perspective
Artificial intelligence (AI)-based devices are increasingly embedded in everyday technologies used by older adults, yet research on AI adoption has largely focused on organizational or domain-specific contexts, leaving everyday use among older populations underexplored. Drawing on Socioemotional Selectivity Theory and digital divide research, this study investigates which socioemotional factors determine older adults’ intention to use AI-based devices. Using survey data from 303 older adults, we analyze how factors as enjoyment, perceived social isolation, or privacy concerns influence performance expectancy and the usage intention. The results show that socioemotional factors act as antecedents of performance expectancy and significantly influence intention to use AI-based devices. By integrating a lifespan perspective with established adoption constructs, this study contributes to IS research by explaining how socioemotional priorities shape technology acceptance in later life and by highlighting implications for the deployment strategy of AI-based technologies to support social connectedness and transparent data practices.
Comments
03-EthicsSocietalImpact