Predicting AI Anxiety: An Existential Perspective

Artificial Intelligence (AI) is transforming many aspects of daily life and improving efficiency and outcomes in various sectors, ranging from healthcare to education. However, this rapid integration also introduces significant anxiety among users, as it undermines their sense of autonomy, identity, meaning, and purpose. The present study examines the associations between key factors and AI anxiety, using self-reported online questionnaires completed by 221 participants. The factors examined included existential reflection, existential anxiety, curiosity and exploration, AI literacy, general anxiety, alongside sociodemographic variables such as gender, age, and job exposure to AI. The measures used were the Existential Reflection Scale (ERS), Existential Concerns Questionnaire (ECQ), Curiosity and Exploration Inventory (CEI), General Anxiety Disorder (GAD), AI Literacy Scale (AIL), and AI Anxiety Scale (AIAS). A multiple regression analysis showed that existential anxiety was the best predictor of AI anxiety, with higher existential anxiety predicting higher AI anxiety (β = .26, p = .004). Higher existential reflection also predicted higher AI anxiety (β = .13, p = .037). Notably, higher AI literacy was found to predict lower AI anxiety (β = −.18, p = .014). Age, gender, job exposure, curiosity and exploration, and general anxiety did not predict AI anxiety. The findings highlight the importance of addressing existential concerns and improving AI literacy to reduce AI anxiety. The study provides a foundation for future research, providing novel insights into AI anxiety and guiding organisations and policy makers to alleviate it.