Paper Number

1086

Paper Type

Complete Research Paper

Abstract

Contrary to fast advancement of artificial intelligence, the mechanism through which AI-assisted systems stimulate positive effects on work performance remains unclear. Drawn on the job characteristic theory and the task-technology fit theory, this paper contends that AI-assisted systems can achieve better fit with work content, positively altering the relations among job characteristics, employee psychological states, and work outcomes. The moderating effect will be further altered by job types in terms of the representation theory. A quasi-experiment is conducted to compare work performance using legacy systems and using RPA (robot process automation) and a PLS-based structural equation modeling technique is employed to test research hypotheses. The results show that the fitness can enhance the relationships between employees’ experienced meaning of work and responsibility for work outcome and their job effectiveness and job satisfaction. This implies that encouraging employees to use AI-assisted systems can generate more intrinsic motivational effects.

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Jun 14th, 12:00 AM

Will AI-Assisted Systems Live Up to Their Fame? An Empirical Investigation of Their Fit with Work Content

Contrary to fast advancement of artificial intelligence, the mechanism through which AI-assisted systems stimulate positive effects on work performance remains unclear. Drawn on the job characteristic theory and the task-technology fit theory, this paper contends that AI-assisted systems can achieve better fit with work content, positively altering the relations among job characteristics, employee psychological states, and work outcomes. The moderating effect will be further altered by job types in terms of the representation theory. A quasi-experiment is conducted to compare work performance using legacy systems and using RPA (robot process automation) and a PLS-based structural equation modeling technique is employed to test research hypotheses. The results show that the fitness can enhance the relationships between employees’ experienced meaning of work and responsibility for work outcome and their job effectiveness and job satisfaction. This implies that encouraging employees to use AI-assisted systems can generate more intrinsic motivational effects.

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