ChatGPT across generations: understanding continued use intention of generative AI technology - Ju, Boryung; Stewart, J. Brenton; Park , Sunyoung (Information Research an international electronic journal, 2026)
Introduction. OpenAI's ChatGPT has revolutionised how people search, organise, and create information in work and daily life. This paper explores how different age groups adopt, use, and sustain their use of ChatGPT and other AI generative technologies. Method. We conducted a cross-sectional online survey of 323 U.S. users of generative AI chatbots to examine individual and collective adoption experiences. Using generational cohort theory, we explored intentions for continued use and the influence of chatbots’ conversational ability, personalisation, social influence, trust, and satisfaction across generations. Analysis. Analysis of variance (ANOVA) and multiple regression were used to analyse the collected data. Results. Trust, social influence, and personalisation significantly affected users’ intention to continue using generative AI chatbots. Significant differences across generations were observed in social influence and conversational ability. Baby Boomers exhibited the lowest levels of social influence but the highest levels of engagement with chatbots’ conversational ability. Conclusions. Baby Boomers (born 1946–1964) are an obscure but enthusiastic cohort among the users of generative AI technologies. Libraries, archives, and museums, among other institutions, should target outreach campaigns at older users, emphasising the potential of AI chatbots to assist users and improve everyday tasks.