AI-metaverse at work: trading value for risk in organizational knowledge systems

Artificial Intelligence (AI) and metaverse technologies are transforming organisational knowledge ecosystems by facilitating immersive, intelligent, and interactive digital work environments. Utilising the theory of consumption value and perceived risk theory, this research formulates and experimentally evaluates two structural models to investigate the impact of AI–metaverse features on knowledge engagement as well as on knowledge application performance. SmartPLS4 was used to look at survey data from 279 professionals who worked in IT, manufacturing, finance, healthcare, education, and retail. The findings indicate that AI–metaverse learning value, cognitive immersion, and enjoyment substantially improve knowledge engagement and subsequent application performance. Conversely, techno-overload surprisingly has a positive effect, implying adaptive behaviour in digitally saturated contexts. On the other hand, information overload, data-surveillance fear, and perceived security vulnerability act as positional non-inhibitors of knowledge engagement. These results enhance theory of consumption value and perceived risk theory by illustrating that cognitive–affective appraisal mechanisms collaboratively influence user engagement in organisational metaverse systems. The paper makes a unique contribution by being one of the first to show how value-driven and risk-based AI-metaverse traits work together to affect organisational knowledge outcomes. This helps us understand both the theory and practice of responsible metaverse-enabled work design.