How Artificial Intelligence Emotional Support Reshapes Employee Interpersonal Relationships: From a Self-Concept Perspective

Abstract

Abstract: With the continuous development of emotional functions in artificial intelligence, the phenomenon of employees seeking emotional support from artificial intelligence is increasing, which will have a profound impact on interpersonal behavior in the workplace. However, compared to the widespread focus on work behavior and outcomes, researches on how artificial intelligence affects employee interpersonal relationships, especially from the perspective of artificial intelligence emotional support, is very limited. Based on the self-concept theory, this study analyzes the data from 440 employees using a three-point questionnaire survey method to explore how artificial intelligence emotional support affects employee relationship reshaping. The research results show that artificial intelligence emotional support can promote employee relationship reflection, thereby facilitating relationship reshaping. The extraversion enhances the positive effect of artificial intelligence emotional support on relationship reflection, while also strengthening the mediating role of relationship reflection between artificial intelligence emotional support and relationship reshaping. Based on the above conclusion, enterprises should pay attention to the potential impact of artificial intelligence emotional functions on the workplace, and effectively plan the application layout of artificial intelligence emotional support based on individual differences of employees, so as to leverage the positive role of artificial intelligence in interpersonal relationships in the workplace.

Key words: artificial intelligence, emotional support, relational reflection, relation reshaping, extroversion

CLC Number:

F272.92

Chen Jia-ying, Xue Jia-xin, Li Yu-hui. How Artificial Intelligence Emotional Support Reshapes Employee Interpersonal Relationships: From a Self-Concept Perspective[J]. Contemporary Finance & Economics, 2026, 0(3): 86-96.

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