Artificial intelligence and work design: implications for frontline service employees and future research

Purpose We examine the impact of artificial intelligence (AI) on the work characteristics of frontline service employees and consider implications for their roles and future research. Design/methodology/approach This conceptual paper draws on insights from prior empirical research on AI in service work. Grounded in socio-technical systems theory, we utilize a five-pronged conceptualization of AI in conjunction with the SMART (Stimulating, Mastery, Autonomous, Relational, Tolerable) Work Design Model to examine the impact of AI on work characteristics. Findings We present evidence from five service sectors: education, finance, healthcare, hospitality and retail. We show that the impact of AI varies across the five higher-level categories of SMART work design and across sectors, revealing context-dependent and technology-specific effects. Practical implications Organizations can optimize service work through top-down redesign and bottom-up crafting, jointly optimizing AI’s characteristics and SMART work characteristics to improve both employee well-being and organizational performance. Originality/value We show the value of SMART work design as a lens to differentiate AI impact on service work and develop a conceptual model of a socio-technical AI–work design system. This model illustrates a dynamic co-design process between AI and work characteristics, with each shaping the other.

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Publication Details

Journal
Journal of service management
Published
2025-11-26
DOI
https://doi.org/10.1108/josm-12-2024-0535
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence and work design: implications for frontline service employees and future research

Stefan Jooss, Annissa Margaret Hansen, Tapani Rinta-Kahila, David Solnet et al.
Journal of service management
AI in Service Interactions
article

Artificial intelligence and work design: implications for frontline service employees and future research

Stefan Jooss, Annissa Margaret Hansen, Tapani Rinta-Kahila, David Solnet, Asha Worsteling, Caroline Knight
article en

Abstract

Purpose We examine the impact of artificial intelligence (AI) on the work characteristics of frontline service employees and consider implications for their roles and future research. Design/methodology/approach This conceptual paper draws on insights from prior empirical research on AI in service work. Grounded in socio-technical systems theory, we utilize a five-pronged conceptualization of AI in conjunction with the SMART (Stimulating, Mastery, Autonomous, Relational, Tolerable) Work Design Model to examine the impact of AI on work characteristics. Findings We present evidence from five service sectors: education, finance, healthcare, hospitality and retail. We show that the impact of AI varies across the five higher-level categories of SMART work design and across sectors, revealing context-dependent and technology-specific effects. Practical implications Organizations can optimize service work through top-down redesign and bottom-up crafting, jointly optimizing AI’s characteristics and SMART work characteristics to improve both employee well-being and organizational performance. Originality/value We show the value of SMART work design as a lens to differentiate AI impact on service work and develop a conceptual model of a socio-technical AI–work design system. This model illustrates a dynamic co-design process between AI and work characteristics, with each shaping the other.

Journal of service management
The University of Queensland (AU), Hanken School of Economics (FI)
Openalex Percentile: Top 80%
AI in Service Interactions
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Artificial intelligence and work design: implications for frontline service employees and future research — Stefan Jooss, Annissa Margaret Hansen, et al. · Journal of service management (2025) | TGRS Research Map | TGRS