Silent signals: does AI adoption encourage or curb quiet quitting in remote work?

Purpose 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.

Authors

Institutions

Publication Details

Journal
Personnel Review
Published
2026-11-03
DOI
https://doi.org/10.1108/pr-12-2025-1403
Primary Topic
Job Satisfaction and Organizational Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Silent signals: does AI adoption encourage or curb quiet quitting in remote work?

Xiaoxia Zhu, Hong Ren, Yu Lu
Personnel Review
Job Satisfaction and Organizational Behavior
article

Silent signals: does AI adoption encourage or curb quiet quitting in remote work?

Xiaoxia Zhu, Hong Ren, Yu Lu
article en

Abstract

Purpose 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.

Personnel Review
Missouri State University (US), University of Wisconsin–Milwaukee (US), Salisbury University (US)
Openalex Percentile: Top 9%
Job Satisfaction and Organizational Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon