Mindfulness and creative self-efficacy in human–AI decision-making: Implications for adaptive AI design

Abstract

Human decision-making is increasingly augmented by artificial intelligence (AI) systems, yet individuals vary in whether they revise their judgments based on AI-generated suggestions. This study provides a timely contribution to the understanding of human factors in AI decision-making, specifically on how two psychological traits i.e. trait mindfulness and creative self-efficacy (CSE), interact with communal-agentic personality orientations to influence decision revision after AI input. Using multinomial logistic regression, we analyzed data from 549 professionals in the United Kingdom to determine whether participants maintained or adjusted their initial decisions following AI advice. Results revealed a significant interaction between mindfulness and CSE. Individuals with high mindfulness and low CSE were more likely to revise their decisions in the direction of AI recommendations, while those high in both traits tended to maintain their original choices. A three-way interaction further showed that this mindfulness–CSE dynamic was most pronounced among individuals scoring high on communal-femininity traits. These findings highlight how attentional focus (mindfulness), perceived creative competence (CSE), and gender-role orientation jointly shape receptivity to AI suggestions. We discuss implications for advancing theory on individual differences in human–AI collaboration and for designing adaptive AI systems tailored to users’ psychological profiles.