Abstract

The emergence of artificial intelligence (AI) is regarded as a revolution in human history: Frenzies have spiked at a remarkable pace as AI chatbots attract a larger number of users shortly after their launch. Despite the many benefits of AI, however, pressure to use AI emerges from various disciplines and diverse perspectives. E.g., pressure may appear in generic workspaces for employees (Loureiro, Bilro et al. 2023). Stress may occur in professional services whose core norms are conventionally not highly technology reliant, such as in interactions via medical monitoring (Park, Werder et al. 2022), or the combat against risks in operations (Singh, Modgil et al. 2024). Some theoretical concepts appear to account for the underlying mechanisms of the pressure to use AI. E.g., information cascades occur when individuals disregard their private information and follow other’s decisions or actions, such as in behaviors observed in scenarios of financial markets (Alevy, Haigh et al. 2007) or in marketing programs (Tuo 2024). In Addition, fear-of-missing-out, a psychological sentiment that individuals experience of fearing being absent, left behind, or excluded from an opportunity or event other people have, is associated with various settings of technology use like in blockchain cryptocurrency (Anaza, Upadhyaya et al. 2024). With pressure being an essential factor for businesses to embrace AI innovation, unfortunately, there lacks a systematic elaboration framing the factors related to pressure coming with the adoption of AI. Hence, in this multidisciplinary research, we have the following research questions: What are factors leading to user pressure, such as ones on individual, organizational, or external levels? Also, how is pressure associated with user satisfaction and task performance in the context of AI adoption? Research plan and expected outcome. This research plans to explore various genres of pressure and the underlying factors associated with them across disciplines from various industries, use settings, and traits of individuals. We anticipate conducting surveys embracing the above scope and hope to uncover factors associated with pressure as a potential obstacle to AI adoption---which will shed insights into the enhancement of AI development and deployment needed to facilitate AI innovation.

Paper Number

tpp1324

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