AI Anxiety and Technostress: The Buffering Role of Growth Mindset

Objective: This study aimed to examine the relationship between AI anxiety and technostress among South African technology users and to determine whether a growth mindset moderates the impact of AI anxiety on technostress. Methods and Materials: A descriptive correlational design was applied with a sample of 440 participants recruited across various professional and academic sectors in South Africa, selected based on the Morgan and Krejcie sampling table to ensure adequate statistical power. Data were collected using standardized instruments: the Technostress Creators Scale (TCS), the AI Anxiety Scale (AIAS), and the Implicit Theories of Intelligence Scale to measure growth mindset. Descriptive statistics were calculated, and Pearson’s correlation examined relationships between variables. Structural Equation Modeling (SEM) with maximum likelihood estimation was performed using AMOS 21 to test the hypothesized moderating effect of growth mindset on the AI anxiety–technostress link. Findings: AI anxiety demonstrated a strong, positive correlation with technostress (r = .63, p < .001), whereas growth mindset was negatively correlated with both technostress (r = –.42, p < .001) and AI anxiety (r = –.47, p < .001). The SEM analysis yielded excellent fit indices (χ²/df = 2.20, GFI = .93, AGFI = .91, CFI = .96, TLI = .95, RMSEA = .052). AI anxiety had a significant positive direct effect on technostress (β = .61, p < .001), while growth mindset showed a significant negative direct effect (β = –.32, p < .001). A significant indirect effect of AI anxiety on technostress through growth mindset (β = –.11, p < .001) confirmed the moderating role of growth mindset. Conclusion: Findings highlight AI anxiety as a critical predictor of technostress and demonstrate that fostering a growth mindset can meaningfully buffer the psychological strain associated with AI-driven environments.