GENERATIVE ARTIFICIAL INTELLIGENCE USE AND EMPLOYEE OUTCOMES: THE MEDIATING ROLE OF COGNITIVE OVERLOAD AND THE MODERATING ROLE OF AI GOVERNANCE CLARITY, (BANKING SECTOR SURVEY)

Abstract

With the emergence of generative artificial intelligence (GenAI) spreading quickly into organizational settings, concerns emerge regarding the overall effect it has on employee experience, performance, and their fair access to benefits. Based on the theory of Conservation of Resources, the paper will explore the cognitive processes by which the use of GenAI affects job performance and job satisfaction and the way AI governance transparency moderates such interactions. Based on survey data of 300 employees based on Partial Least Squares Structural Equation Modeling (PLS-SEM), it was found that the use of GenAI is positively related to job performance and job satisfaction, but also has a major impact on cognitive overload. Cognitive overload, in its turn, has negative implications on the outcomes and partially mediates the relationships between GenAI use and employee outcomes. More importantly, AI governance clarity moderates the connection between GenAI use and cognitive overload, with clarity of governance having a significant negative effect on cognitive strain. These results indicate that, although GenAI can positively impact the workplace outcome, the positive effect is partly neutralized by the augmented cognitive load. Transparent and evident forms of governance turn out to be a major organizational asset to curb negative cognitive consequences and renew more inclusive and accommodating GenAI adoption conditions. The research study makes contributions to the theory by connecting the cognitive processes to governance situations in AI research, and provides practical information to organizations interested in implementing the GenAI tools in a responsible and equitable environment.