The IS research community has introduced and used several theoretical models and constructs to investigate information technology (IT) adoption and use behaviors in individuals. At this point in time, the community requires coherent guidance towards conceptual and methodological considerations that have the potential to provide new insights into the changing nature of interactions between people and technology. These changes are mostly related to the fact that technology is becoming more of an intelligent agent than a mere tool. Thus, the aim of this paper is to distinguish between IT and artificial intelligence (AI) artifacts and to discuss its implications for IS research on AI adoption and use behaviors. Using UTAUT, D&L IS success model, and TTF as examples, we argue how well-established models used in IS research may need to evolve to capture adoption and use behaviors of people who use or intend to use AI artifacts.