KnE Social Sciences

ISSN: 2518-668X

The latest conference proceedings on humanities, arts and social sciences.

Drivers of Artificial Intelligence (AI) Adoption in Tourism Companies: An Empirical Study of Technology Acceptance Model (TAM) Theory

Published date: Dec 03 2025

Journal Title: KnE Social Sciences

Issue title: The 5th International Conference on Tourism, Gastronomy, and Tourist Destination (TGDIC 2025)

Pages: 115 - 124

DOI: 10.18502/kss.v10i29.20257

Authors:

Renza Fahlevirenza.fahlevi@uib.ac.idBatam International University, Batam

Lily PurwiantiBatam International University, Batam

Agus RiyadiTrisakti Institute of Tourism, Jakarta

Willy ArafahTrisakti Institute of Tourism, Jakarta

Ariendy FilrandoBatam International University, Batam

Abstract:

Competition among AI providers is intensifying, with each offering its own unique features to users. This study aims to examine AI usage behavior among tourism companies. Two variables, perceived ease of use (PE) and perceived usefulness (PU) are used to measure their influence on intention to use (ITU) and actual use (AU). Respondents in this study were AI users from tourism companies, who are increasingly using AI to help generate engaging and relevant marketing content. The sample size was 225, determined using a purposive sampling approach. The research data was processed using a Structural Equation Modeling (SEM) approach with SmartPLS software. The research findings indicate that both independent variables, PE and PU, influence ITU and AU, both directly and indirectly. This finding confirms previous findings, which showed that the perceived usefulness of using AI technology is the strongest variable influencing intention to use AI by tourism companies. This research contributes to AI providers’ understanding of user needs in the tourism sector, enabling them to develop more tailored products or features. Furthermore, the study results provide strategic guidance for tourism companies in adopting AI to improve operational efficiency, customer experience, and business competitiveness. Theoretically, this study broadens the understanding of the determinants of AI adoption in the tourism industry and opens up opportunities for further research related to digital innovation in the service sector.

Keywords: perceived ease of use, perceived usefulness, intention to use, actual usage

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