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

Yuheng Ren, Safiya Mukhtar Alshibani, Varun Chotia, Bhumika Gupta () and Amedeo Maizza
Additional contact information
Yuheng Ren: JMU - Jimei University [Fujian, China], Xiamen Jianpan Kunlu Internet of Things Research Institute Xiamen
Safiya Mukhtar Alshibani: Princess Nourah Bint Abdulrahman University
Varun Chotia: Jaipuria Institute of Management [Noida]
Bhumika Gupta: LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], ETHOS - Ethique, Technologies, Humains, Organisations, Société - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]
Amedeo Maizza: Università del Salento = University of Salento [Lecce]

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Abstract: 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.

Keywords: Organizational knowledge systems; Immersive work environments; Theory of consumption value; Perceived risk theory; Techno-overload; Cognitive immersion; Knowledge application performance; Knowledge engagement; AI–metaverse systems (search for similar items in EconPapers)
Date: 2026-06
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Published in Technology in Society, 2026, 85, pp.103202. ⟨10.1016/j.techsoc.2025.103202⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05456520

DOI: 10.1016/j.techsoc.2025.103202

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