Generative AI Usage, AI Literacy, and Employee Performance in Parsa’s Industrial and Trading Enterprises

Abstract

Purpose: Generative AI adoption is transforming organizational performance globally, yet its influence on employee outcomes depends heavily on AI literacy rather than usage alone.

Methods: Existing studies focus on corporate, educational, or Chinese contexts, leaving Nepal’s industrial and trading sector, particularly Parsa District, unexplored. This quantitative study used Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0 and SPSS 20. Data were collected from 105 employees of Parsa’s industrial and trading enterprises using convenience sampling.

Results: Generative AI Usage significantly predicts AI Literacy, which significantly predicts Employee Performance; however, the direct effect of Generative AI Usage on performance was non-significant, confirming full mediation. Field observations show limited practical AI literacy despite basic awareness, grounded in AMO and Social Cognitive theories. AI Literacy, not mere access, drives performance gains.

Originality/Value: This study validates the mediation model within Nepal’s underexplored Terai-Madhesh context. Longitudinal and cross-sector studies are recommended to generalize these findings.