Employee Performance and Artificial Intelligence

Ng, Zhuo Ming (2024) Employee Performance and Artificial Intelligence. Masters thesis, Tunku Abdul Rahman University of Management and Technology.

Text 05 Ng Zhuo Ming (MBA).pdf Restricted to Registered users only Download (1MB)

Abstract

The digital revolution has already had an impact by converting the world into a modern one characterised by data dominance in all commercial activities. Advanced information and communication technologies (ICT), such as Artificial Intelligence-powered tools, have been widely deployed in service organisations to improve service delivery. This study aims to investigate the factors that influence employee performance among Malaysians. A quantitative approach using questionnaires was adopted for this study. A total of 220 questionnaires were collected around Malaysia. The results showed that artificial intelligence service performance and high performance work practice have a significant influence on employee engagement. Moreover, only artificial intelligence service performance has a significant influence on the employee service quality. Furthermore, only employee engagement has a significant influence on employee performance while employee service quality does not. The mediating variable such as employee engagement has a significant mediating effect on the relationship between high performance work practice and employee performance but not significant mediating the relationship between artificial intelligence service performance and employee performance. Moreover, employee service quality has a significant mediating effect on the relationship between artificial intelligence service performance and employee performance. Besides that, job security has a significant moderating effect on the relationship between artificial intelligence service performance and employee service quality but not significant moderating the relationship between artificial intelligence service performance and employee service quality. This study extended the goal setting theory and social exchange theory to improve the predictive of the model. This study also helps supervisors and employees to better understand the relationship between Artificial Intelligence service performance, employee engagement, and employee performance by showcasing how technology can be used to improve employee engagement and employee performance. The limitations and future studies were also discussed in this study.