Discerning authenticity through symbolic and natural stimuli: an integrated servicescape model for AI service apps

Purpose Artificial intelligence (AI)-powered service apps are widely adopted but raise critical authenticity concerns, particularly as human-facing AI increasingly simulates social presence and care. This study aims to explore how customers discern authenticity through symbolic and natural stimuli, moving beyond technical perspectives. Design/methodology/approach A sequential mixed-method design combining in-depth interviews (n = 26) and text mining (N = 11,400 reviews) is conducted, focusing on health, beauty and lifestyle sectors. Interviews identified symbolic and natural stimuli, while topic modeling assessed their relative importance in comparison with physical and social stimuli. Findings We developed an integrated servicescape model incorporating physical, social stimuli with the new four symbolic stimuli (monetization strategy, situational/cultural fit, moral commitment, recommendation precision) and three natural stimuli (service realism, soothing interactions, safe disclosure environments). The findings reveal asymmetric effects on customer engagement valence, showing how different stimuli are associated with positive vs negative engagement. Practical implications The model guides app developers, service designers and marketers to strategically embed symbolic and natural stimuli that strengthen authenticity and foster sustained and positively valenced customer engagement. Social implications This study supports the creation of more transparent, trustworthy and inclusive AI service ecosystems. Originality/value Building on and extending the stimulus–organism–response framework and servicescape literature, this research identifies previously underexplored symbolic and natural stimuli beyond physical and social factors. It demonstrates how these stimuli shape customer engagement valence in AI-powered service apps, offering fresh insights into contemporary service authenticity.