Risks related to Artificial Intelligence in service experience: a bibliometric analysis and development of a conceptual framework for the premium service context
Vol. 135 No. 5D (2026), Original Article
Vol. 135 No. 5D (2026)

Risks related to Artificial Intelligence in service experience: a bibliometric analysis and development of a conceptual framework for the premium service context

Original Article
https://doi.org/10.26459/hueunijed.v135i5D.8573
Published 2026-10-19
Nguyen Thi Ha
School of Hospitality and Tourism, 22 Lam Hoang St., Hue City, Viet Nam
Nguyen Quyet Thang
Ho Chi Minh City University of Technology, 475A Dien Bien Phu St., Thanh My Tay Ward, Ho Chi Minh City, Vietnam

Keywords

artificial intelligence
perceived risk
trust
experiential value
premium services

Abstract

The integration of artificial intelligence (AI) into service touchpoints both enhances efficiency and personalization capabilities and creates risks that can degrade the premium service experience. This study identifies the knowledge structure, the level of development of topics, and the mechanisms of risk formation related to AI, thereby proposing a conceptual framework connecting AI risks, trust, and experiential value. Data comprises 390 publications collected from Web of Science from 2021 to June 20, 2026. Bibliometrix/Biblioshiny was used for descriptive statistics, keyword co-occurrence analysis, topic mapping, and co-citation analysis of relationships among documents, authors, and keywords. The results show that the cluster of trust, acceptance, and intention holds a prominent position, while tourism, technology, and hospitality form the contextual foundation of the sector. This conceptual synthesis identifies four risk mechanisms: algorithmic lack of transparency, data and privacy asymmetry, diminished control, and dehumanization of the experience. Drawing on conservation of resources (COR) theory and a customer journey approach, the study proposes trust as a theoretical mediating mechanism between AI risk and experiential value. The results contribute to connecting fragmented research streams and provide a basis for customer-centric AI governance in premium services.

https://doi.org/10.26459/hueunijed.v135i5D.8573

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