Silent signals: does AI adoption encourage or curb quiet quitting in remote work?
Lu Yu, Xiaoxia Zhu, Hong RenPurpose
This study examines how organisational artificial intelligence (AI) adoption shapes quiet quitting (QQ) among remote workers, using conservation of resources (COR) theory to specify when AI curbs versus encourages QQ.
Design/methodology/approach
We conducted a three-wave survey of 693 remote employees and tested a moderated dual pathway model in which organisational AI adoption relates to QQ via psychological empowerment and technostress, conditional on proactive personality.
Findings
Organisational AI adoption increased psychological empowerment and reduced QQ among highly proactive employees, but reduced empowerment and increased QQ among less proactive employees. In contrast, AI adoption uniformly heightened technostress, which was positively related to QQ regardless of proactivity. Proactive personality therefore strengthened AI's benefits but did not offset its technostress costs.
Originality/value
We position QQ as a resource regulation response to AI enabled work conditions, conceptualise organisational AI adoption as a double edged contextual demand that simultaneously generates empowerment and technostress and show that proactive personality shapes only the empowerment pathway. The findings extend COR theory to emerging workplace technologies and highlight empowerment and stress mitigation by design for resource sustaining remote work.