What makes an app authentic? Determining antecedents of perceived authenticity in an AI-powered service app
Diem-Trang Vo, Long Thang Van Nguyen, Duy Dang-Pham, Ai-Phuong Hoang
Abstract
Mobile applications integrated with artificial intelligence play a vital role in engaging users with the services thanks to their ability to perform natural interactions and conduct various tasks. Despite users’ quest for authenticity, limited studies have explored the notion of authenticity of this non-human humanlike touchpoint. Study 1 (n = 331) explores the four dimensions of authenticity in the context of AI-powered service apps. Using regulatory engagement and parasocial interaction theory, study 2 (n = 309) confirms media richness, parent brand attitudes, and co-branding fit as influencing factors of perceived authenticity in the context of AI-powered service apps. The six solutions from fsQCA reveal the different but equally important combinations of media, brand, endorser, and personal factors to achieve a high perception of authenticity. This study contributes to the algorithmic experience literature by extending the idea of “proper means” in the AI-powered context. • The study uses heuristic-systematic model of the algorithmic process, parasocial interaction, regulatory engagement theory. • The authenticity concept in AI context goes beyond social presence and includes credibility, integrity, and symbolism. • Media richness, co-branding fit, and parent-brand attitude are antecedents for authenticity in AI-powered service apps. • Different combinations of media, brand, social, and personal factors can foster the perception of authenticity. • This research contributes to algorithmic experience, authenticity, and engagement literature.