Employees' learning behavior in the context of AI collaboration: a perspective on the job demand-control model

Abstract

Purpose

Most studies have focused on the impact of the application of AI on management attributes, management decisions and management ethics. However, how job demand and job control in the context of AI collaboration determine employees' learning process and learning behaviors, as well as how AI collaboration moderates employees' learning process and learning behaviors, remains unknown. To answer these questions, the authors adopted a Job Demand-Control (JDC) model to explore the influencing factors of employee's individual learning behavior.

Design/methodology/approach

This study used questionnaire survey in organizations using AI to collect data. Partial least squares (PLS) predict algorithm and SPSS were used to test the hypotheses.

Findings

Job demand and job control positively influence self-efficacy, self-efficacy positively influences learning goal orientation and learning goal orientation positively influences learning behavior. Learning goal orientation plays a mediating role between self-efficacy and learning behavior. Meanwhile, collaboration with AI positively moderates the impact of employees' job demand on self-efficacy and the impact of self-efficacy on learning behavior.

Originality/value

This study introduces self-efficacy as the outcome of JDC model, demonstrates the mediating role of learning goal orientation and introduces collaborative factors related to artificial intelligence. This study further enriches the theoretical system of human–AI interaction and expands the content of organizational learning theory.

Citation

Chen, A., Yang, T., Ma, J. and Lu, Y. (2023), "Employees' learning behavior in the context of AI collaboration: a perspective on the job demand-control model", Industrial Management & Data Systems, Vol. 123 No. 8, pp. 2169-2193. https://doi.org/10.1108/IMDS-04-2022-0221