From autonomous vehicles to smart home assistants and telemedicine, artificial intelligence enabled (AI-enabled) technologies are increasingly available in the market. Consumers are saddled between the benefits and the risks of these new technologies, yet prior research has not accounted for the coexistence of inhibitory and faciliatory factors and how they affect intentions to use AI-enabled technology. The current research introduces a conceptual model to address these relationships and integrates the role of subjective ambivalence and brand trust. The model was tested using structural equation modeling with a cross sectional survey of U.S. consumers across three distinct categories of AI: autonomous vehicles for robotic AI, smart home assistants for virtual AI, and telemedicine for embedded AI. The findings reveal that the coexistence of the facilitators and inhibitors gives rise to ambivalence, which itself affects the adoption of novel technology and that brand trust also plays a critical role in affecting facilitators and inhibitors. Theoretical and practical implications are discussed in terms of the diffusion of innovation and the psychological processes that underlie consumer adoption of new technologies often laden in ambivalence.
Library of Congress Subject Headings
Artificial intelligence; Branding (Marketing); Consumers -- United States
Date of Award
Graziadio Business School
Dagliyan, George, "Adoption of AI-enabled technology: taking the bad with the good" (2021). Theses and Dissertations. 1240.