AI sensation and engagement: Unpacking the sensory experience in human-AI interaction

Abstract

Given the limited studies on AI sensation and its impact on consumer emotional response and engagement, we investigate its impact to drive engagement. Employing a mixed-methods approach, we began with a qualitative phase consisting of 68 interviews (18 healthcare employees, 37 users of Wearable Health Devices, 7 AI developers, and 6 academics). Grounded in the theories of constructed emotion and the uncanny valley, as well as insights from the qualitative phase, we developed a robust model investigating the role of AI sensation on costumer emotional responses and engagement. This was followed by a survey of 557 healthcare employees. Data analysis was conducted using SPSS for descriptive statistics and reliability assessments, and AMOS for confirmatory factor analysis to validate the robustness of our measurement models. our findings show that AI sensation can drive customer subjective feeling state and AI affects. We also found empirical evidence that both can mediate the relationship between AI sensation, customer subjective feeling state, AI affects and activation engagement. Our findings can offer valuable understanding for managers and AI developers, underscoring the important role of AI sensation for driving engagement.