Paper Number
ICIS2025-2228
Paper Type
Teaching
Abstract
This teaching case traces the AI-driven transformation of re:spondelligent, a Swiss startup specializing in customer feedback management for the hospitality sector. Originally offering fully manual, high-quality review responses written by professional authors, the company embarked on a multi-year journey to integrate AI incrementally into its operations. Through a collaborative innovation project, re:spondelligent developed tools for sentiment analysis, response quality control, automated drafting, and difficulty scoring. These tools not only streamlined internal workflows but also enabled the company to transform its business model – introducing a tiered service offering and a triage system aligned with review complexity and client preferences. The case illustrates how small firms can leverage dynamic capabilities and combinatorial innovation to adapt in rapidly changing technological environments. It invites discussion on strategic AI integration, business model transformation, and the human-AI balance in service delivery.
Recommended Citation
Katsiuba, Dzmitry; Dolata, Mateusz; Crowston, Kevin; and Schwabe, Gerhard, "Adopt, Adapt, Transform: AI Integration in Customer Feedback Management" (2025). ICIS 2025 Proceedings. 15.
https://aisel.aisnet.org/icis2025/learn_curricula/learn_curricula/15
Adopt, Adapt, Transform: AI Integration in Customer Feedback Management
This teaching case traces the AI-driven transformation of re:spondelligent, a Swiss startup specializing in customer feedback management for the hospitality sector. Originally offering fully manual, high-quality review responses written by professional authors, the company embarked on a multi-year journey to integrate AI incrementally into its operations. Through a collaborative innovation project, re:spondelligent developed tools for sentiment analysis, response quality control, automated drafting, and difficulty scoring. These tools not only streamlined internal workflows but also enabled the company to transform its business model – introducing a tiered service offering and a triage system aligned with review complexity and client preferences. The case illustrates how small firms can leverage dynamic capabilities and combinatorial innovation to adapt in rapidly changing technological environments. It invites discussion on strategic AI integration, business model transformation, and the human-AI balance in service delivery.
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