Working with AI: the impact of organizational intelligent service strategy on employees’ perception of career achievement

Jiaqi Xu, Xiaofei Tang, En-Chung Chang and Haoyu Peng ()
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Jiaqi Xu: Southwestern University of Finance and Economics
Xiaofei Tang: Southwestern University of Finance and Economics
En-Chung Chang: Renmin University of China
Haoyu Peng: University of Peradeniya

Palgrave Communications, 2024, vol. 11, issue 1, 1-20

Abstract: Abstract In the artificial intelligence (AI) environment, there is limited research on employees’ perception of career achievement. Previous literature has presented two different viewpoints: AI either reduces or increases employees’ perception of career achievement. We introduce the concept of the intelligent service strategy to resolve this contradiction and explore its underlying reasons. Through three experiments involving 736 front-line employees (with valid responses of 223, 232, and 281 for each study, respectively), this research reveals the influence of organizational intelligent service strategy (substitution vs. collaboration) on employees’ perception of career achievement. To elucidate, compared with the intelligence collaboration service strategy, the intelligence substitution service strategy decreases human–human interactivity and enhances human–machine interactivity, thus reducing employees’ perception of career achievement. Intriguingly, the organizational innovation climate significantly moderates the relationship between (human–human and human–machine) interactivity and employees’ perception of career achievement. Specifically, the organizational innovation climate might mitigate the positive effect of human-human interactivity and the negative effect of human-machine interactivity on the perception of career achievement. This research provides a finer-grained understanding of how employees perceive career achievement when working with AI, thus explaining conflicting conclusions drawn in previous studies. These insights contribute innovatively to the theoretical framework concerning employees’ intrinsic motivations within the intelligent service environment.

Date: 2024
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DOI: 10.1057/s41599-024-03265-1

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