TITLE:
Emotional Predictors of AI Adaptation: A Quantitative Analysis of Fear, Uncertainty, and Resistance among U.S. Adults
AUTHORS:
Michelle Rozen
KEYWORDS:
AI Anxiety, Behavioural Response Adaptation, Perceived Uncertainty, Technology Acceptance, Technostress
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.13 No.9,
September
8,
2025
ABSTRACT: A number of psychological issues, such as worries about job displacement, the perceived danger to human autonomy, and fears of bias and misuse, are the root causes of the fear and anxiety surrounding the adoption of AI. It is essential to comprehend these psychological obstacles in order to promote adoption and the responsible integration of AI technologies. With this in mind, the study intends to quantitatively examine how people’s adoption response behaviours among US adults relate to their perceived fear and uncertainty about AI. The study employs a large-scale quantitative research design, with a sample size 5000 participants. A robust descriptive quantitative, correlational research design is adopted in this study. The quantitative results indicate that worry, perplexity, and a tendency to mistrust AI are the main issues and cause substantial societal adoption friction. These issues go beyond technical skill deficiencies to encompass extremely complex psychological issues and pinpoint erosion worries. By proving that uncertainty is a crucial and independent predictor of technology adoption, the acquired results support the inclusion of the existing Technology Acceptance Model in the larger theoretical framework for research on digital transformation.