AI awareness, AI fear of missing out, and work demotivation as pathways to occupational strain in Vietnamese hospitality employees.

Artificial intelligence (AI) is reshaping hospitality work and changing how employees perceive occupational risks and their capacity to adapt. How these AI-related perceptions translate into employee strain, however, remains poorly understood. Drawing on the Job Demands-Resources and Conservation of Resources frameworks, this study examines a sequential motivational mechanism linking AI awareness and digital self-efficacy to occupational strain through two psychological states: AI fear of missing out (AI FoMo), defined as anxiety about falling behind in accessing and using AI, and work demotivation. Survey data from an online purposive sample of 459 Vietnamese hospitality employees (2025) were analyzed using two-stage PLS-SEM, with occupational strain modeled as a second-order formative construct of job burnout and job insecurity. In this sample, the higher-order construct reflected a composite strain condition dominated by burnout while also incorporating elements of job insecurity. AI awareness was negatively related to AI FoMo but showed no significant direct association with strain, indicating that it operates through downstream psychological states rather than directly. AI FoMo was, in turn, linked to higher work demotivation and strain, and work demotivation to higher strain, supporting a serial pathway in which falling-behind anxiety erodes the motivational energy that then accumulates as strain. Digital self-efficacy played a consistent protective role, relating negatively to AI FoMo, work demotivation, and strain alike. Multi-group analysis suggested some variation across demographic groups, but these differences are treated as exploratory given limited measurement invariance. Because the design is cross-sectional, these associations cannot confirm causal ordering; nonetheless, they suggest that easing AI FoMo through transparent communication and building digital self-efficacy through job-specific training are practical levers for reducing strain during AI transition in the hospitality sector.