Fear of missing out on AI: A psychological cost of technological revolution
• Newly developed English FOMO-AI scale shows strong psychometric properties. • One in nine U.S. adults report elevated FOMO-AI, especially younger adults and women. • Higher AI literacy buffers against FOMO-AI, while attitudes toward AI show no effect. • FOMO-AI predicts depressive and anxiety symptoms and reduces well-being. Artificial intelligence (AI) is transforming education, healthcare, governance, and work at unprecedented speed, but such rapid development also raises new psychological and societal challenges. One emerging concern is fear of missing out on AI (FOMO-AI) – the worry that one’s AI skills or access lag behind others. This study validates an English FOMO-AI scale in a U.S. adult sample ( N = 557) and applies it to address three questions: (1) What is the prevalence and demographic distribution of FOMO-AI? (2) How do AI literacy and attitudes shape FOMO-AI? (3) Does FOMO-AI predict mental-health and well-being outcomes? Findings showed that although most people fortunately reported low FOMO-AI, a meaningful minority (more than one in nine) endorsed elevated levels, with younger adults and women being more vulnerable. Furthermore, AI literacy, but not general attitudes toward AI, emerged as the central mechanism shaping FOMO-AI, with higher literacy buffering against it and lower literacy exacerbating it. Importantly, FOMO-AI predicted greater anxiety and depressive symptoms, which, in turn, reduced well-being. Together, these results highlight FOMO-AI as a new, measurable psychological cost of technological revolution and underscore that the future of AI is not only a technological challenge but also a human one.
Authors
- Chi‐Lin Yu (ORCID: https://orcid.org/0000-0002-4381-7163)
Institutions
- Oklahoma State University Oklahoma City (US)
Publication Details
- Journal
- Telematics and Informatics Reports
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1016/j.teler.2025.100277
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65