Assessing the impact of Generative AI Use on Employee Job Performance

Generative AI (GAI) is driving the next wave of technological transformation in the business sector, and many companies have begun using it across various business functions. It is now mandatory for employees to use GAI to perform various tasks and meet job performance requirements. However, the understanding of how GAI is helping to improve their job performance remains unexplored. This empirical research examines the factors influencing employees' self-efficacy and its contribution to their job performance by validating a model grounded in social cognitive theory, including cognitive aspects of employees and GAI attributes. A survey of 405 employees and their line managers was conducted, and the data were analyzed using PLS-SEM. The results indicate that self-directed learning, GAI literacy, perceived intelligence, and perceived personalization positively influence employees' self-efficacy, while technological anxiety negatively influences the use of GAI. Further, it was found that self-efficacy has a positive association with employee's job performance, and this relationship is negatively moderated by hallucination potential. This study enhances understanding of GAI use at the workplace and human-GAI dynamics in relation to employee job performance. This research provides insights for top management, organizational managers, and GAI marketers, developers, and designers.