A study of artificial intelligence service performance on job performance in the information technology industry: the mediating roles of job engagement and employee creativity

Abstract

Artificial Intelligence (AI) is a rapidly evolving field that has gained significant attention in recent years due to its potential to revolutionize various industries. Drawing on a variety of theories, including Resource-Based View Theory (RBT) and Boundary-Crossing Theory (BCT), that have been applied to underpin these relationships, the study proposes AI tools as boundary-crossing objects to investigate how AI service performance can affect employees' job engagement, creativity, and job performance. It also confirms the mediator of job engagement and creativity in the relationship between AI service performance and job performance. The Partial Least Squares - Structural Equation Modeling (PLS-SEM) with a twostage approach was used for data analysis using SmartPLS 4.0. This study was conducted using both qualitative and quantitative research methods with a total of 312 valuable respondents who work for IT companies and experience using AI tools at work. The results indicate that AI service performance significantly affected employees' job engagement and creativity, which in turn increased employees' job performance. Additionally, there were significant mediating effects between AI service performance and job performance, as evidenced by job engagement and creativity. The study contributes new quantitative research on AI service performance and outcomes to the knowledge library, especially in the IT industry, which lacks such studies. The results have managerial implications for business owners, top managers, or employees evaluating the potential benefits of integrating AI into their operations.