Why AI does not always enhance employee creativity: Metacognitive calibration and AI engagement in human–AI innovation systems
Artificial intelligence (AI) is widely assumed to enhance creativity in knowledge work, yet empirical findings reveal substantial variability in its effects. Addressing this inconsistency, the present study advances a metacognitive explanation by integrating metacognitive calibration theory with AI engagement research. We propose that calibration bias, the discrepancy between perceived and actual cognitive competence, influences creativity indirectly through behavioral engagement with AI systems as algorithmic support tools. Drawing on social cognitive theory, we develop a mediation model in which calibration bias predicts AI engagement, which in turn predicts supervisor-rated creativity. We further examine whether AI use intensity moderates this relationship. Using a time-lagged, multi-source design, data were collected from 437 employees nested within 58 supervisors in Islamic banking institutions and analyzed using Mplus-based structural modeling. Calibration bias positively predicts AI engagement, which in turn enhances creativity. Bootstrapped mediation analysis indicates a significant positive indirect effect of calibration bias on creativity through AI engagement, supporting partial mediation. However, AI use intensity does not significantly moderate the relationship between calibration bias and AI engagement. The findings contribute to theory by extending metacognitive calibration research into AI-augmented organizational contexts and reframing AI-assisted creativity as a metacognitively contingent process within AI-enabled work systems rather than a purely technological outcome. By identifying AI engagement as the behavioral mechanism linking metacognitive discrepancy to creative performance, this study advances a process-based understanding of human–AI collaboration.
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