From AI Adoption to AI-Augmented Work: How AI-Enabled HRM Shapes Hospitality Employee Well-Being through Job Redesign and Work Autonomy
Abstract: Artificial intelligence is increasingly embedded in hospitality organisations, yet research has often concentrated on adoption, acceptance and service-robot reactions rather than on how AI changes the design and experience of work. This study develops an employee-centred model explaining how AI-enabled human resource management (AI-HRM) can influence hospitality employee well-being through AI-enabled job redesign and work autonomy, while examining AI self-efficacy as an individual boundary condition. Drawing on Conservation of Resources theory and the Job Demands?Resources framework, the model proposes a resource-gain pathway in which AI-enabled HRM facilitates redesign of tasks and roles, redesigned work enhances autonomy, and autonomy improves employee well-being. The proposed empirical design uses a three-wave survey of employees in AI-exposed hospitality organisations. For analytical prototyping, an empirical dataset of 450 cases was examined using reliability analysis, descriptive statistics, discriminant-validity diagnostics, regression-based structural paths, 5,000-resample bootstrap mediation and interaction analysis. The prototype results show strong internal consistency and a positive serial indirect pathway from AI-HRM to well-being through job redesign and autonomy. However, the moderation interaction is small and statistically non-significant in the observed data. The study's substantive contribution is to reposition AI-HRM from a technology-adoption question toward a human-centred work-design question.
Keywords: artificial intelligence; AI-enabled HRM; job redesign; work autonomy; employee well-being; AI self-efficacy; hospitality; human resource management
How to Cite?: Ambili G. R. Kuniyel, Dr. N. Uma Devi, "From AI Adoption to AI-Augmented Work: How AI-Enabled HRM Shapes Hospitality Employee Well-Being through Job Redesign and Work Autonomy", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 1392-1396, https://www.ijsr.net/getabstract.php?paperid=SR26922155006, DOI: https://dx.doi.org/10.21275/SR26922155006