JOB CRAFTING, MEANINGFUL WORK, AND PROMOTIVE VOICE IN THE ERA OF ARTIFICIAL INTELLIGENCE: A CONDITIONAL PROCESS ANALYSIS

Abstract

The rapid integration of artificial intelligence (AI) into workplaces is reshaping job design and employee behaviour. This study examines how employees' proactive job redesign efforts (job crafting) translate into promotive voice behaviour through meaningful work and whether AI-related job insecurity moderates this relationship.  Using a dataset (N = 312), this study tested a moderated mediation model via PROCESS macro in SPSS. Normality, reliability, and validity tests were conducted. Job crafting, meaningful work, AI-related job insecurity, and promotive voice were measured using validated scales. Job crafting significantly predicted meaningful work. Meaningful work positively predicted promotive voice and mediated the job crafting–voice relationship. AI-related job insecurity negatively moderated the meaningful work–voice relationship such that the relationship was stronger under low insecurity (slope = 0.67, p < .001) and weaker under high insecurity. The conditional indirect effect was supported (H5), with the indirect effect decreasing from 0.29 under low insecurity to 0.12 under high insecurity. This study integrates job crafting, meaningful work, and employee voice literatures with emerging AI-at-work research. It demonstrates that AI-related job insecurity can suppress voice even among employees who find their work meaningful, addressing a critical gap in future-of-work scholarship. Organizations implementing AI should reduce AI-related insecurity through transparency, reskilling, participatory design, and psychological safety interventions to ensure that meaningful work continues to inspire constructive voice.