How to manage AI and human input in customer feedback systems without eroding empathy and trust
File(s)
Accepted version (Journal pre-proof)
Author(s)
Washington, Bodicia
Merlo, Omar
Prados Spitaleri, Valentina
Eisingerich, Andreas B
Type
Journal Article
Abstract
Artificial intelligence (AI) is increasingly embedded in customer feedback systems, promising speed, scale, and predictive insight. Yet many organizations struggle to integrate AI without eroding empathy, trust, and relational quality. This paper examines how managers balance AI-driven efficiency with human judgment in customer feedback management. Drawing on twenty semi-structured interviews across government, healthcare, marketing, finance, and technology sectors, we surface five interconnected findings: AI’s operational power as a high-volume extraction engine; its structural limitation of nuance blindness in contextual interpretation; the counterintuitive finding that human involvement introduces its own distortions and is not a reliable corrective; AI’s underutilized role as a governance stabilizer that depoliticizes decisions and legitimizes authority; and AI’s upstream influence in reshaping the generative conditions of feedback itself, altering what people are willing to say and to whom. Building on these insights, we develop a structured hybrid playbook outlining how managers can design, govern, and audit human–AI feedback systems. The playbook offers actionable guidance on task allocation, escalation protocols, accountability roles, and governance mechanisms that allow firms to scale intelligence without sacrificing empathy. The findings position AI not as a replacement for human judgment, but as a complementary engine for service improvement when deliberately orchestrated.
Date Issued
2026-05-28
Date Acceptance
2026-05-24
Citation
Business Horizons, 2026
ISSN
0007-6813
Publisher
Elsevier
Journal / Book Title
Business Horizons
Copyright Statement
© 2026 Kelley School of Business, Indiana University. Published by Elsevier Inc. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Identifier
10.1016/j.bushor.2026.05.012
Publication Status
Published online
Date Publish Online
2026-05-28