Content area
The integration of Generative Artificial Intelligence (GenAI) into professional environments is rapidly transforming individual workflows, decision-making processes, and productivity. This study explores the impact of GenAI tools on individual performance by applying the Information Systems Success Model (DeLone & McLean, 2003) and Protection Motivation Theory (Rogers, 1975). A research model was developed incorporating system quality, information quality, and service quality as antecedents of system use and user satisfaction. Additionally, social well-being was introduced as a mediating variable between use/satisfaction and individual performance, while perceived vulnerability and response cost from PMT were tested as moderators. Data was collected through an online survey with 764 valid responses and analyzed using Partial Least Squares Structural Equation Modeling (PLSSEM). The results confirm the dual importance of use and satisfaction in predicting performance and highlight social well-being as a key emotional mechanism. The study contributes to IS literature by integrating psychological and emotional dimensions into models of AI adoption and offers practical insights into the human-centered implementation of GenAI tools in the workplace.