Hybrid human-AI coaching: experiences of coaches and agents in a customer service environment

Most studies on AI coaching focus on AI as an independent system. Instead, this study examines the implementation of hybrid AI-supported coaching, where an AI-tool supports but does not replace the human coach. We evaluate how coaches and workers experience the implementation of AI-supported coaching, and what factors shape trust and perceived effectiveness. We use an inductive thematic analysis of qualitative interviews with both coaches and workers one month and five months after implementation of the AI-tool. The evaluation focuses on four themes: Two themes refer to the coaches: AI integration and Coaching effectiveness; and two themes refer to the agents: Trust dynamics and Feedback-driven growth. Our findings reveal an initial phase of resistance, linked to concerns about surveillance, followed by growing trust and perceived value due to the tool’s ability to generate feedback that was perceived as more objective, consistent, and more relevant than the traditional subjective feedback of coaches. Although adoption required additional effort, the tool enabled more targeted preparation, precise feedback, and measurable learning outcomes. Transparent use and the active involvement of coaches who build their coaching on the AI-generated data further supported this transition. Trust in the AI-supported coaching was built through ongoing human engagement.

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Publication Details

Journal
Coaching An International Journal of Theory Research and Practice
Published
2025-11-14
DOI
https://doi.org/10.1080/17521882.2025.2588290
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Hybrid human-AI coaching: experiences of coaches and agents in a customer service environment

Andries de Grip, Sanne Steens, Marie-Christine Fregin, Stijn Horck et al.
Coaching An International Journal of Theory Research and Practice
AI in Service Interactions
article

Hybrid human-AI coaching: experiences of coaches and agents in a customer service environment

Andries de Grip, Sanne Steens, Marie-Christine Fregin, Stijn Horck, Danique Eijkenboom
article en

Abstract

Most studies on AI coaching focus on AI as an independent system. Instead, this study examines the implementation of hybrid AI-supported coaching, where an AI-tool supports but does not replace the human coach. We evaluate how coaches and workers experience the implementation of AI-supported coaching, and what factors shape trust and perceived effectiveness. We use an inductive thematic analysis of qualitative interviews with both coaches and workers one month and five months after implementation of the AI-tool. The evaluation focuses on four themes: Two themes refer to the coaches: AI integration and Coaching effectiveness; and two themes refer to the agents: Trust dynamics and Feedback-driven growth. Our findings reveal an initial phase of resistance, linked to concerns about surveillance, followed by growing trust and perceived value due to the tool’s ability to generate feedback that was perceived as more objective, consistent, and more relevant than the traditional subjective feedback of coaches. Although adoption required additional effort, the tool enabled more targeted preparation, precise feedback, and measurable learning outcomes. Transparent use and the active involvement of coaches who build their coaching on the AI-generated data further supported this transition. Trust in the AI-supported coaching was built through ongoing human engagement.

Coaching An International Journal of Theory Research and PracticeVol. 19(1)
IZA - Institute of Labor Economics (DE), Maastricht School of Management (NL), Maastricht University Medical Centre (NL), Maastricht University (NL)
Openalex Percentile: Top 82%
AI in Service Interactions
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Hybrid human-AI coaching: experiences of coaches and agents in a customer service environment — Andries de Grip, Sanne Steens, et al. · Coaching An International Journal of Theory Research and Practice (2025) | TGRS Research Map | TGRS