Humanized artificial intelligence in tourism: drivers of traveler adoption and value co-creation
Purpose Inspired by service-dominant logic (SDL) theory and the unified theory of acceptance and use of technology (UTAUT), this study examines how humanized AI attributes, namely conversational intelligence, anthropomorphism and information quality, shape the motivations of tourists to engage with AI. These motivations encompass value, convenience, superior functionality, ubiquity and personalization. It further investigates how these motivational factors influence tourists' perceived value co-creation when utilizing AI-enabled services. It explores how perceived value co-creation shapes tourists' behavioral intentions to adopt AI-driven tourism services. Design/methodology/approach Based on variance-based structural equation modeling (PLS-SEM), data were obtained from 713 Egyptian participants with previous experience using AI for travel. The data capture participants' perceptions and behavioral tendencies regarding the use of AI in travel contexts. Findings AI systems that include human-like features such as being relatable, having conversation skills and providing valuable information help tourists see their value. Tourists enjoy high-value co-creation with AI when it provides personalization, convenience, better functionality, and ubiquity. This co-created value drives their intention to adopt AI-powered travel planning services. Practical implications Tourism stakeholders and policymakers should develop humanized, personalized and ubiquitous AI tools underpinned by ethical data management, user-friendliness and public-private collaboration. Value co-creation, tourist trust, satisfaction and behavioral engagement on digital tourism platforms can be improved through capacity-building programs and human-centered AI design. Originality/value This study advances SDL and extends UTAUT by demonstrating how humanized AI attributes drive tourist motivations, value co-creation and behavioral intentions, offering guidance for designing personalized and interactive AI-enabled tourism services.
Authors
- Ahmed Mohamed Elbaz (ORCID: https://orcid.org/0000-0002-3106-7182)
- Islam Elbayoumi Salem (ORCID: https://orcid.org/0000-0002-9483-3550)
- Omar Durrah (ORCID: https://orcid.org/0000-0002-8923-9450)
- Khalid Salim Al Shanfari (ORCID: https://orcid.org/0009-0005-5739-8683)
- Badawy S.Y. Sayed (ORCID: https://orcid.org/0009-0007-1204-3912)
- Maha Misbah Mohamed Shabana
Institutions
- Damietta University (EG)
- University College Birmingham (GB)
- University of Sadat City (EG)
- College of Tourism (BG)
- Higher Institute for Tourism, Hotels and Computer (EG)
- Dhofar University (OM)
- College of Business Administration (LV)
Publication Details
- Journal
- Journal of Hospitality and Tourism Insights
- Published
- 2026-08-21
- DOI
- https://doi.org/10.1108/jhti-12-2025-1456
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00