Hybrid human-AI coaching: experiences of coaches and agents in a customer service environment
Danique Eijkenboom et al.
What the paper says
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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.