Studying the Adoption of AI Artifacts

Over the past three decades, there has been an extensive interest in studying users’ adoption and use of Information technology (IT). Many theories have been developed, and numerous variables have been considered. A question today is whether these theories and models are appropriate for the study of users’ adoption and use of Artificial Intelligence (AI) based technologies? In this paper, we discuss the foundational elements of a new theory. Our proposed theory consists of four distinct components: 1) the determinants of the interaction, which include task, user, and technology characteristics, 2) the structure of interaction, which represents how the user chooses to interact with the technology, and the resulting beliefs formed about the characteristics of the technology based on that interaction, 3) the interaction outcomes and evaluations, which represent the beliefs formed about the outcomes of using the technology as well as an evaluation of the relationship with it, and 4) the dynamic component, which models how evaluative beliefs formed or updated in one interaction can affect how the technology is utilized in subsequent interactions.