(untitled) (Third Sector Social Economic Review, 2026)
The effect of technological applications on the performance of digital transformation processes of enterprises and the psychological and organizational mechanisms through which this effect is realized have not been adequately explained. This study examines the effect of employees’ Artificial Intelligence-oriented Digital Transformation Perceptions (AIDA) on Individual Job Performance (BIP) and Organizational Performance (PP) and the mediating role of motivation in this relationship. This study aims to provide a human-centered perspective by analyzing whether the impact of AI-driven digital transformation perception on employees’ performance outcomes is direct or through employee motivation. The sample of this quantitative study consists of blue and white-collar employees working in banking institutions in Istanbul. Data were collected from 284 participants through a structured 26-item questionnaire. The data obtained were analyzed by Structural Equation Modeling (PLS-SEM) approach with Partial Smallest Method using SmartPLS 4 software. In the evaluation of the measurement model, Cronbach’s Alpha, composite reliability (CR) and mean explained variance (AVE) values were taken into account. For the structural model, path coefficients, t- and p-values from bootstrapping, as well as SRMR, NFI, and GoF indices, were assessed. The results show that EPADT has a significant positive effect on both IBP and OP, and that employee motivation mediates the relationship between IBP and OP. These findings highlight the importance of employee motivation in successful digital transformation.