Crossing the Digital Divide: Understanding Older Adults' Technology Acceptance of Generative Artificial Intelligence: A Qualitative Study
The diffusion of generative artificial intelligence is redefining the relationship between older adults and digital technologies. Existing studies have largely explained the digital divide among older adults through traditional digital media such as smartphones and mobile payment, while insufficient attention has been paid to how conversational artificial intelligence changes older adults' entry thresholds, sustained-use motivations, and risk-judgment mechanisms. This study adopts a multimethod qualitative desig…

In brief
Researchers interviewed 40 people aged 60 and over in two towns of Songjiang District, Shanghai, in early 2026, and also observed them on digital scenario tasks. They examined how conversational AI changes older adults' entry into digital technology, their reasons for continued use, and how they judge risk.
The findings matter because they suggest the digital divide for older adults is not closed by easier interfaces alone. Whether people actually cross it depends on skills such as checking sources and judging the limits of AI answers. The sample is small and local, so how far the pattern holds elsewhere is unknown.
Main points
- The study used semistructured interviews plus scenario-based digital tasks with 40 participants aged 60 and above.
- Participants had internet experience and tended toward frequent smartphone use.
- Sustained use was linked to emotional anchoring, experience organization, relationship maintenance, and concrete tasks, not efficiency alone.
- Community support, peer learning, and intergenerational help helped people move from trial to stable use.
- The authors propose a 'conditional crossing' mechanism and call for age-friendly governance that builds capability and risk support.
The gain
Conversational AI moves the barrier from operating interfaces to articulating needs and evaluating results, letting some older adults use their life experience and language skills to get around interface limits.
The rundown
Fieldwork ran from January to February 2026 in Chedun Town and Xinqiao Town in Shanghai's Songjiang District. Data included interview transcripts, task-observation records, screenshots of AI conversations, and field notes, analyzed thematically.
To strengthen credibility, the team triangulated these sources and used an initial coding manual, double review, and consensus discussion.
The authors argue that crossing the divide depends on developing source verification, contextual delimitation, and boundary judgment. They conclude that age-friendly governance should move past interface simplification toward capability enhancement and risk support.
Sources
- Peer-reviewedThe International Journal of Aging and Human Development2026-10-16
ace
The debate