AI-Induced occupational uncertainty as a multi-level challenge: reconciling human-centered values with automation in tourism and hospitality

This study examines AI-induced occupational uncertainty in the tourism and hospitality industry. A qualitative multi-level critical synthesis that combines critical reflection with narrative synthesis was applied to examine the pervasive effects of AI-induced job insecurity across individual, organizational, familial, and societal dimensions. The objective is to problematize the efficiency narrative of AI and uncover hidden socio-technical costs. AI adoption creates a double-edged sword effect, where operational gains offset psychological stress, familial relational strain, and deepening societal inequality. This study contributes a novel four-level synthesis framework and advocates for agile policy interventions, including participatory co-design, targeted reskilling, and universal social protections. By shifting the discourse from technical implementation to human dignity, this research provides a holistic diagnostic tool for industry leaders and policymakers to align technological innovation with the core human-centric values of hospitality.