How the Terminator might affect the car manufacturing industry: Examining the role of pre-announcement bias for AI-based IS adoptions

The steep development of artificial intelligence (AI) is accompanied by a completely new set of challenges for information systems (IS) research and practice, especially in the area of individual-level technology adoption. In this article, we elaborate on the important role that biases play regarding the adoption of AI-based IS by individuals in a work environment and for which, in addition, an alarmingly early occurrence within the overall process can be reported. Based on an exploratory case study within three different German car manufacturers, we credit this work with a valuable threefold contribution. First, it introduces and substantiates knowledge and theory on the pre-announcement phase of individual-level IS adoption. Second, it is one of the very few works that thoroughly conceptualize and analyze the role of biases in user decision making resulting from the individuals' cognitive limitations. And third, it indicates a notable spillover effect of experiences and opinions on AI from the users' private lives to their professional ones, which stands in clear contrast to what usually is reported in IS research. The article thereby discusses general implications for IS theory but also elaborates on the AI-specific elements regarding IS implementations in a professional environment.

Automated summary

This article discusses the challenges brought by the rapid development of artificial intelligence in the adoption of technology at an individual level. It focuses on the role of biases and examines their impact on user decision making. Through a case study of three German car manufacturers, the article highlights the importance of the pre-announcement phase in information systems adoption and provides a comprehensive analysis of biases caused by individuals' cognitive limitations. It also reveals a notable spillover effect of users' experiences and opinions on AI from their personal lives to their professional lives, which contradicts previous findings in IS research.