The Impact of Generative Artificial Intelligence Use on Anxiety Among Young Workplace Populations: A Mediation Study Based on Job Insecurity

Abstract

The rapid integration of generative artificial intelligence tools, such as OpenAI's ChatGPT and Anthropic's Claude, into contemporary professional settings has raised significant concerns regarding their profound psychological impact on young workers. As organizations increasingly automate complex cognitive tasks, emerging professionals face unprecedented challenges in navigating their career trajectories. This study rigorously investigates whether and how the frequent use of generative AI technologies influences anxiety levels among young workplace populations, with a particular focus on the mediating role of job insecurity. Drawing comprehensively on job insecurity theory and the Technology Acceptance Model (TAM), this research conceptualizes job insecurity as a multidimensional construct encompassing perceived job replacement risk, perceived skill devaluation, and broader career uncertainty. Using extensive secondary data extracted from established, publicly available labor market and occupational databases, the study employs advanced structural equation modeling to systematically examine both the direct effect of generative AI use on workplace anxiety and its indirect effect through the lens of job insecurity. The empirical findings provide robust evidence for the mediating mechanism linking AI adoption to adverse psychological outcomes among young workers, demonstrating that heightened technological exposure significantly exacerbates fears of obsolescence. Ultimately, this research contributes to the growing literature on AI and workplace mental health by identifying job insecurity as a critical pathway through which generative AI tools shape worker well-being. Strategic implications for organizational support systems, targeted psychological interventions, and responsible future AI implementation are thoroughly discussed.