Balancing truth and lies: ethical management of AI in service encounters
Purpose This article aims to investigate the management of artificial intelligence (AI) as a frontline service technology in service encounters and its associated ethical aspects. It specifically examines the phenomenon of lying by proxy, in which AI, under human direction, may distort the truth to varying degrees, from white lies to significant fabrications. Design/methodology/approach Using a conceptual approach, the study reviews existing literature on deceptive behaviors in service encounters and explores AI's dual potential as both a substitute for and complement to frontline employees. It employs illustrative mini cases to demonstrate how the proposed conceptual framework applies to real-world contexts, emphasizing AI's role in service delivery. Findings The paper introduces a framework to guide organizations in the ethical use of AI within service encounters. It emphasizes the importance of aligning AI applications with ethical standards to preserve trust and legal compliance while highlighting AI's potential to enhance customer experiences without breaching ethical limits. Research limitations/implications From a managerial perspective, the study provides guidance on the ethical deployment of AI in service encounters, offering strategies to balance enhanced customer experiences with transparency and honesty. Theoretically, it extends the understanding of service encounters by recognizing AI not merely as a passive frontline service technology but as an active participant capable of shaping service interactions through its capacity for deception. Originality/value This work contributes to the discourse on service management, ethics and customer experience by demonstrating how AI can be strategically managed to lie by proxy in a controlled and ethically responsible manner. The proposed framework and accompanying research agenda offer directions for future studies on integrating AI as a frontline service technology, ensuring that AI strengthens rather than undermines customer and societal trust in business.
Authors
- Hannah Snyder (ORCID: https://orcid.org/0000-0002-6604-2727)
- Thomas Magor (ORCID: https://orcid.org/0000-0002-2169-4692)
- Ursula Bougoure
- Allard C.R. van Riel
- Lars Witell
- Shannon Lutze
Institutions
- Linköping University (SE)
- The University of Queensland (AU)
- BI Norwegian Business School (NO)
- Hasselt University (BE)
Publication Details
- Journal
- Journal of service management
- Published
- 2026-01-08
- DOI
- https://doi.org/10.1108/josm-12-2024-0538
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00