Reconceptualizing employee AI awareness as a multidimensional construct: beyond job displacement
Selim Bakir, Tarik Dogru, Anil Bilgihan, Baker AyounPurpose
This study aims to critically review how hospitality research has conceptualized employee artificial intelligence (AI) awareness and offer a reconceptualization that moves beyond a narrow, job-displacement focus to a multidimensional view encompassing both adverse and beneficial implications of AI integration for employees’ jobs, careers and well-being.
Design/methodology/approach
The study adopts a narrative synthesis of recent hospitality and related organizational research on employee AI awareness, integrating conceptual and empirical work across disciplines and drawing on multiple theoretical perspectives, including the Job Demands–Resources model, uncertainty management theory, self-determination theory and dynamic capability and task-level replacement frameworks.
Findings
Existing hospitality studies predominantly frame employee AI awareness as a threat linked to job insecurity, burnout and turnover intentions, often conflating distinct constructs and focusing on replacement-centric outcomes. This study reconceptualizes employee AI awareness as a multidimensional construct, encompassing awareness of AI tools, task-substitution awareness and role-ambiguity awareness, with both dark and bright pathways that can produce negative outcomes (e.g. strain, withdrawal, occupational health and mental health symptoms) or positive outcomes (e.g. creativity, job crafting, engagement, thriving and human–AI collaboration), contingent on available resources, appraisals and contextual factors.
Research limitations/implications
As a conceptual review grounded primarily in recent hospitality literature, the proposed framework requires empirical validation and refined measurement of the distinct facets of employee AI awareness. The article outlines a future research agenda spanning measurement boundaries, causal micro-mechanisms, technology design features, cross-level implementation and temporal career dynamics to build cumulative evidence on how employee AI awareness shapes behavior and well-being over time.
Practical implications
The multidimensional reconceptualization enables hospitality managers to differentiate between displacement-related strain and AI usage or role-ambiguity stress, informing targeted interventions such as reskilling, AI literacy training, supportive leadership and fair communication about AI-enabled job redesign. Managers can use the framework as a diagnostic tool to monitor how AI integration affects employees’ well-being, attitudes and behaviors and to design organizational resources that convert AI-related demands into opportunities for growth and engagement.
Social implications
This study highlights pathways for more sustainable and humane AI adoption in hospitality workplaces. This broader lens enables organizations and policymakers to anticipate the distributional effects on career trajectories and mental health and to support more inclusive strategies for preparing employees for AI-intensive service environments.
Originality/value
To the best of the authors’ knowledge, this study provides one of the first hospitality-focused, theory-driven reconceptualizations of employee AI awareness, clarifying terminological ambiguities and separating key dimensions and outcomes. It integrates underutilized organizational theories into a comprehensive, multi-perspective framework and offers an agenda that repositions employees as active agents who learn, adapt and co-create value with AI, rather than as passive victims of technological disruption.