Year: 2025
Type: conference-paper
Abstract: This study delves into the dynamics among customers and GenAI in services focusing on service failure recovery. It reveals that customers accept GenAI’s apologies and how such apologies resemble/differ from human apologies. It also offers a model of an apology that companies can use based on the severity of the situation. Finally, the study provides tactics for service providers to enhance GenAI-driven service recovery.
Author: Azer, Jaylan
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7038750601
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