Warning to AI washing: a mixed-method study on the antecedents and consequences of AI washing perception towards AI-powered services in hospitality and tourism

With increasing technological competition, companies have exaggerated their technological capabilities by overusing the term artificial intelligence (AI) as a buzzword, leading to AI washing issues. This study is thus designed to examine the antecedents and consequences of AI washing perception, focusing on the hospitality and tourism contexts. More specifically, the study conducted (1) a hypothetico-deductive method with a quantitative analysis to examine the consequences of AI washing perception and (2) a qualitative approach with inductive content analysis to explore the antecedents of AI washing perception. The data was collected from a total of 472 respondents, including 238 hotel goers and 234 tourists. The results of a quantitative analysis revealed that AI washing perception is causally related to trust and negative word-of-mouth intentions, and trust is causally related to switching intentions and negative word-of-mouth intentions. The results of a qualitative analysis revealed that low innovativeness, provider-centered, and perceived risks are associated with AI washing perception. The study consequently presents a comprehensive understanding of AI washing perception in the hospitality and tourism context.