Keeping up with generative AI: effects of engagement characteristics, cognitive appraisals, and affective reactions on user adaptation

Xinyu Lu and Jisu Kim

Behaviour and Information Technology, 2025, vol. 44, issue 18, 4523-4537

Abstract: Generative artificial intelligence (GenAI) is expected to substantially change users’ established routines of accomplishing tasks, such as information search and content creation. Despite such promising potential, many users are still not incorporating GenAI into their routine internet use. This study draws on the adaptation to information technology (AIT) model to examine how users adapt to GenAI and the influencing factors, including cognitive appraisals, affective reactions, and engagement characteristics. An online survey was conducted with GenAI users recruited on Prolific. The results showed that cognitive appraisals (perceived opportunity, threat, and control) and affective reactions (enjoyment, trust, and anxiety) influence users’ various adaptations to varying degrees. Furthermore, engagement characteristics, including the frequency and breadth of using GenAI tools and user involvement, are significant predictors of cognitive appraisals. The study contributes to the nascent literature on GenAI tools by uncovering the impact of cognitive appraisals and affective reactions on users’ adaptation to GenAI tools, meanwhile revealing the influence of engagement characteristics on users’ appraisals. The findings provide a basis for encouraging certain adaptation behaviours and help understand factors that hinder users’ active adaptation to GenAI.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2025.2483788 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:44:y:2025:i:18:p:4523-4537

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2025.2483788

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().