The sound of progress: AI voice agents in service

Purpose This article advances research on artificial intelligence (AI)-powered voice agents (hereafter, AI voice agents) by providing (1) a conceptualization of AI voice, (2) a conceptual mapping of AI voice agents, and (3) an organizing framework outlining key benefits, risks, and contingency factors associated with AI voice agents in service. This introduction to the special issue on “Voice Capabilities in Smart Service Systems” also outlines future research directions for AI voice agents in service and beyond. Design/methodology/approach Drawing on insights from marketing and management literature complemented with communications, linguistics, and human–computer interaction research, the article describes voice elements relevant for service research. The conceptual mapping and the organizing framework guide the future research agenda. Findings First, AI voice is conceptualized through verbal (i.e. diction, syntax, semantics) and paraverbal elements (i.e. pitch, volume, speech rate, pauses, pronunciation, articulation, timbre, and breathiness). Next, the proposed typology maps AI voice agents by voice richness and AI intelligence. Finally, the conceptual framework articulates benefits (e.g. interactivity, social presence, convenience, personalization, enjoyment) and risks (e.g. intrusiveness, privacy concerns, algorithmic bias) associated with AI voice agents, and introduces relevant contingency factors covering user, voice technology, service setting, and ecosystem characteristics. Originality/value The paper offers a clear definition of AI voice, as well as a conceptual mapping that enables service researchers to systematically classify and compare AI voice agents. Moreover, the study highlights key pathways that may inspire future work.

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Institutions

Publication Details

Journal
Journal of service management
Published
2025-09-09
DOI
https://doi.org/10.1108/josm-06-2025-0269
Citations
4
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
9.92
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article

The sound of progress: AI voice agents in service

Dominik Mahr, Bieke Henkens, Arne De Keyser, Carsten D. Schultz
4 citations
Journal of service management
AI in Service Interactions
9.92
article

The sound of progress: AI voice agents in service

Dominik Mahr, Bieke Henkens, Arne De Keyser, Carsten D. Schultz
article en
4 citations

Abstract

Purpose This article advances research on artificial intelligence (AI)-powered voice agents (hereafter, AI voice agents) by providing (1) a conceptualization of AI voice, (2) a conceptual mapping of AI voice agents, and (3) an organizing framework outlining key benefits, risks, and contingency factors associated with AI voice agents in service. This introduction to the special issue on “Voice Capabilities in Smart Service Systems” also outlines future research directions for AI voice agents in service and beyond. Design/methodology/approach Drawing on insights from marketing and management literature complemented with communications, linguistics, and human–computer interaction research, the article describes voice elements relevant for service research. The conceptual mapping and the organizing framework guide the future research agenda. Findings First, AI voice is conceptualized through verbal (i.e. diction, syntax, semantics) and paraverbal elements (i.e. pitch, volume, speech rate, pauses, pronunciation, articulation, timbre, and breathiness). Next, the proposed typology maps AI voice agents by voice richness and AI intelligence. Finally, the conceptual framework articulates benefits (e.g. interactivity, social presence, convenience, personalization, enjoyment) and risks (e.g. intrusiveness, privacy concerns, algorithmic bias) associated with AI voice agents, and introduces relevant contingency factors covering user, voice technology, service setting, and ecosystem characteristics. Originality/value The paper offers a clear definition of AI voice, as well as a conceptual mapping that enables service researchers to systematically classify and compare AI voice agents. Moreover, the study highlights key pathways that may inspire future work.

Journal of service managementVol. 37(1)
FernUniversität in Hagen (DE), Maastricht School of Management (NL), Maastricht University (NL), Eindhoven University of Technology (NL), Ecole des Hautes Etudes Commerciales du Nord (FR)
Openalex Percentile: Top 2%
AI in Service Interactions
9.92
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