Empowering or Pressuring? How AI-Supported Leadership Shapes Procrastination Through Self-Efficacy and Anxiety

• In Event: Labor and Labor Movements Section Refereed Roundtables
  In Refereed Roundtable (60 minute): Roundtable 4: Devotion, Discipline, and Inequality in Contemporary Labor Regimes

Abstract

This study investigates how AI-supported leadership shapes procrastination at work through two psychological routes grounded in social cognitive theory. It proposes a dual-pathway model in which self-efficacy reduces procrastination while anxiety increases it, and tests whether trust in AI conditions these effects. A two-wave survey was administered to 325 employees. Path analysis tested the moderated mediation framework, estimating indirect effects via self-efficacy and anxiety and the moderating role of trust in AI. AI-supported leadership related to lower procrastination through higher self-efficacy and to higher procrastination through heightened anxiety. Trust in AI significantly strengthened the positive pathway by amplifying the link between AI-supported leadership and self-efficacy, and significantly weakened the negative pathway by attenuating the link between AI-supported leadership and anxiety. The conditional indirect effects mirrored these patterns. The study advances research on AI and employee self-regulation by identifying concurrent cognitive and affective mechanisms linking AI-supported leadership to procrastination. It clarifies when these effects unfold by establishing trust in AI as a pivotal boundary condition, offering guidance for designing AI-enabled leadership practices that build efficacy while containing anxiety.

Authors

• Chuanyi Luan, Harbin Institute of Technology

• Xinglan Yang

• Li Zhang