Psychological resistance to AI: How regulatory focus fuels AI anxiety and negative attitudes toward AI

Abstract

As artificial intelligence (AI) becomes increasingly embedded in the socio-economic and technological structure of society, it presents both significant opportunities and notable threats for entrepreneurs. Because business ideas emerge through ongoing interaction between entrepreneurs and their communities, it is crucial to understand the psychological mechanisms that shape not only entrepreneurs’ AI-related attitudes but also those of key stakeholders such as customers and investors. While emerging research tends to adopt a generally optimistic stance, with attention to AI’s risks largely confined to post-adoption concerns, our study shifts the lens upstream by investigating the antecedents of psychological resistance to AI adoption. Specifically, we explore the psychological mechanisms underlying AI anxiety and negative attitudes toward AI. Drawing on regulatory focus theory, status quo bias, and the emotion-as-information framework, we theorize that prevention focus is positively associated with negative attitudes toward AI, and that this relationship is partially mediated by four dimensions of AI anxiety: learning anxiety, job replacement anxiety, sociotechnical blindness, and configuration anxiety. We test our model using data from 259 undergraduate entrepreneurship students at a U.S. university and find empirical support for our hypotheses. We encourage entrepreneurship research to examine how cognitions, motivations, and affect shape resistance to AI, as this shift can clarify why some entrepreneurs fail to engage with transformative technologies. Our study contributes by foregrounding motivational and affective barriers to AI engagement, offering guidance for reframing AI to resonate with individuals with high prevention focus, and urging educators to consider students’ underlying anxieties and aversions to AI. • Psychological resistance to AI adoption persists despite growing optimism about its societal and economic benefits. • Prevention focus is associated with negative attitudes toward AI. • AI anxiety, specifically, learning, job replacement, configuration, and sociotechnical blindness, partially mediates this effect. • The model draws on regulatory focus theory, status quo bias perspective, and the emotion-as-information framework. • Empirical support is found using data from 259 students taking entrepreneurship classes at a U.S. university.

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