The Psychological Impact of AI on Managerial Decision Confidence: A Behavioral Study

Abstract

The increasing integration of artificial intelligence (AI) into organizational decision-making has significantly transformed managerial processes, particularly in enhancing decision confidence. This study examines the psychological impact of AI-supported decision systems on managerial decision confidence by analysing the roles of technological usage, psychological perceptions, behavioural responses, and individual differences. Drawing on the Technology Acceptance Model (TAM), Attribution Theory, and Signaling Theory, a comprehensive framework is developed to explain how AI influences managerial cognition and confidence.
A quantitative research design was adopted using a structured questionnaire administered to 280 managerial professionals across multiple industries. Data were analysed using SPSS, employing descriptive statistics, reliability and validity testing, correlation, regression, and moderation analysis through PROCESS Macro Model 1. The findings reveal that AI-supported decision systems usage has a significant positive effect on managerial decision confidence (β = 0.415, p < 0.001), explaining 17.3% of the variance. Among psychological factors, trust in AI (β = 0.484, R² = 0.235) and perceived reliability (β = 0.471, R² = 0.222) exert strong positive effects, while risk perception has a significant negative impact (β = −0.364, R² = 0.133). Behavioural responses also play a critical role, with AI reliance positively influencing decision confidence (β = 0.377, R² = 0.142) and AI resistance negatively affecting it (β = −0.363, R² = 0.131). However, moderation analysis indicates that managerial experience (β = 0.073, p = 0.190) and familiarity with AI (β = 0.033, p = 0.567) do not significantly moderate the relationship between AI usage and decision confidence.
The study contributes to the literature by extending TAM to post-adoption cognitive outcomes and integrating psychological and behavioural dimensions into AI-supported decision-making research. Practically, the findings highlight the importance of fostering trust, minimizing perceived risks, and encouraging constructive engagement with AI systems to enhance managerial effectiveness.
Keywords: Artificial Intelligence, Managerial Decision Confidence, Trust in AI, Perceived Reliability, Risk Perception, AI Reliance, AI Resistance, Technology Acceptance Model (TAM).