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Service Recovery Strategies in Cases of AI Malfunction
0
Zitationen
2
Autoren
2025
Jahr
Abstract
As AI technologies become increasingly integral to diverse service industries, understanding how to effectively address and recover from AI failures is paramount. Drawing upon an extensive review of the literature and empirical evidence, this chapter elucidates the multifaceted challenges inherent in service recovery when AI malfunctions. It explores various dimensions of AI malfunction scenarios, encompassing technical failures and misinterpretation of data. Moreover, a 2×2 matrix is provided for plotting service malfunctions in terms of severity and impact as well as providing practical strategies for orchestrating robust service recovery processes in such circumstances. By integrating insights from AI ethics, crisis management and service management literature, this scholarly inquiry offers valuable guidance to practitioners, managers, and policymakers in formulating proactive and responsible approaches to mitigate the adverse impacts of AI failures on service quality, customer satisfaction, and organisational reputation.
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