When AI improves and impairs performance: role stress and regulatory focus in service work

Purpose This study aims to investigate how artificial intelligence technology integration (AITI) affects employees’ task performance through two distinct role-stress mechanisms – role conflict and role overload – and whether these relationships vary according to employees’ chronic regulatory focus (CRF). Design/methodology/approach An explanatory sequential mixed-methods design was adopted. First, a two-wave survey was conducted among hotel employees and their supervisors to test the hypothesized model quantitatively. Second, a follow-up qualitative case study based on semi-structured interviews was used to further interpret the quantitative findings in real service settings. Findings AITI was found to enhance task performance by increasing role overload, while simultaneously impairing task performance through increased role conflict. Moreover, CRF moderated the effects of AITI on both forms of role stress. Compared with promotion-focused employees, prevention-focused employees experienced stronger effects of AITI on role conflict and role overload, resulting in stronger indirect effects on task performance. Practical implications Managers should move beyond a purely efficiency-driven approach to AI adoption and pay closer attention to employees’ role perceptions and motivational orientations. Organizations should reduce AI-related role conflict through clearer role design, training and support, while channeling manageable role overload into learning, adaptation and performance improvement. Tailored management practices for prevention- and promotion-focused employees may further enhance AI implementation outcomes. Originality/value This study offers a novel explanation of how AITI simultaneously improves and impairs task performance by uncovering two contrasting role-stress mechanisms. By integrating role theory and regulatory focus theory in a mixed-methods design, it provides a richer understanding of employee–AI interaction in service work.

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Publication Details

Journal
International Journal of Contemporary Hospitality Management
Published
2026-07-30
DOI
https://doi.org/10.1108/ijchm-07-2025-1101
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

When AI improves and impairs performance: role stress and regulatory focus in service work

Xiaojun Wu, Yingji Zhang, Chiyin Chen
International Journal of Contemporary Hospitality Management
Ethics and Social Impacts of AI
article

When AI improves and impairs performance: role stress and regulatory focus in service work

Xiaojun Wu, Yingji Zhang, Chiyin Chen
article en

Abstract

Purpose This study aims to investigate how artificial intelligence technology integration (AITI) affects employees’ task performance through two distinct role-stress mechanisms – role conflict and role overload – and whether these relationships vary according to employees’ chronic regulatory focus (CRF). Design/methodology/approach An explanatory sequential mixed-methods design was adopted. First, a two-wave survey was conducted among hotel employees and their supervisors to test the hypothesized model quantitatively. Second, a follow-up qualitative case study based on semi-structured interviews was used to further interpret the quantitative findings in real service settings. Findings AITI was found to enhance task performance by increasing role overload, while simultaneously impairing task performance through increased role conflict. Moreover, CRF moderated the effects of AITI on both forms of role stress. Compared with promotion-focused employees, prevention-focused employees experienced stronger effects of AITI on role conflict and role overload, resulting in stronger indirect effects on task performance. Practical implications Managers should move beyond a purely efficiency-driven approach to AI adoption and pay closer attention to employees’ role perceptions and motivational orientations. Organizations should reduce AI-related role conflict through clearer role design, training and support, while channeling manageable role overload into learning, adaptation and performance improvement. Tailored management practices for prevention- and promotion-focused employees may further enhance AI implementation outcomes. Originality/value This study offers a novel explanation of how AITI simultaneously improves and impairs task performance by uncovering two contrasting role-stress mechanisms. By integrating role theory and regulatory focus theory in a mixed-methods design, it provides a richer understanding of employee–AI interaction in service work.

International Journal of Contemporary Hospitality Management
Donghua University (CN), Nankai University (CN), School of Business and Management (FR)
Openalex Percentile: Top 6%
Ethics and Social Impacts of AI
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