How the Terminator might affect the car manufacturing industry: Examining the role of pre-announcement bias for AI-based IS adoptions
Demlehner Q, Laumer S (2024)
Publication Type: Journal article
Publication year: 2024
Journal
Book Volume: 61
Article Number: 103881
Journal Issue: 1
Abstract
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.
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Germany (DE)How to cite
APA:
Demlehner, Q., & Laumer, S. (2024). How the Terminator might affect the car manufacturing industry: Examining the role of pre-announcement bias for AI-based IS adoptions. Information & Management, 61(1). https://doi.org/10.1016/j.im.2023.103881
MLA:
Demlehner, Quirin, and Sven Laumer. "How the Terminator might affect the car manufacturing industry: Examining the role of pre-announcement bias for AI-based IS adoptions." Information & Management 61.1 (2024).
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