Generational engagement with AI in hospitality
Human–AI interaction perspectives across the service process
Bibliographic Data
| ID | 21698513 |
|---|---|
| Authors | Pola Q Wang (0000-0002-2435-7755, Auckland University of Technology, corresponding author), Liwei Yan (Auckland University of Technology), Carolin Santoso (Auckland University of Technology) |
| Year | 2026 |
| Volume | 29 |
| Issue | 7 |
| Pages | 1281-1294 |
| Publication date | 2026-04-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Current Issues in Tourism (JOURNAL) |
| Journal identifiers | ISSN: 1368-3500 • E-ISSN: 1747-7603 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/13683500.2025.2528981 |
| OpenAlex | W4412034253 |
| Language | EN |
| References cited | 45 |
As artificial intelligence (AI) becomes increasingly integrated into hospitality and tourism operations, it is essential to understand how employees from different generational cohorts engage with AI technologies in the workplace. This conceptual study introduces a generationally responsive framework to examine human AI engagement across three key service phases: pre-arrival, mid-arrival, and post-arrival. It distinguishes between two overarching modes of engagement: interaction, which includes coexistence, cooperation, and collaboration, and collaboration itself, which involves complementarity and augmentation models. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the framework applies four key dimensions: performance expectancy, effort expectancy, social influence, and facilitating conditions to explain how generational characteristics influence AI perceptions and behaviours. A unique contribution of this study is the identification of an emerging autonomous decision support model, especially relevant for Generation Z, in which AI makes and implements service decisions independently with minimal human involvement. These generational patterns vary across service tasks and reflect broader differences in digital fluency, workplace expectations, and trust in technology. The study concludes that effective AI integration in hospitality requires alignment with the values, preferences, and interaction styles of a multigeneration workforce
Business · Customer engagement · Hospitality · Hospitality industry · Knowledge management · Political science · Public relations · Social media · Sociology · Tourism · World Wide Web · AI in Service Interactions · Computer Science · Digital Marketing and Social Media · Halal products and consumer behavior · Psychology · Marketing
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Aging and Information Technology Use
User Acceptance of Information Technology
Consumer Acceptance and Use of Information Technology
Digital Natives, Digital Immigrants Part 1
Generational differences
Migrant mobility and value creation in hospitality labour
Artificial Intelligence in Hospitality and Tourism
| Citation velocity | historical |
|---|---|
| Highly cited | No |