This study integrates Haslam’s (2006) dual-process model of dehumanization and Organizational Justice Theory (Greenberg, 1987) to examine the impact of artificial intelligence (AI) on workplace dehumanization in the hospitality and tourism industries. It highlights how the implementation of AI in human resource management (HRM) may erode fairness, identity, and emotional connection in service-oriented environments.
This study follows a critical narrative review approach. It synthesizes interdisciplinary literature from hospitality, psychology, and AI ethics to identify patterns of dehumanization associated with AI systems in guest-facing and human resources (HR) contexts.
Fewer than a dozen empirical studies have directly examined this intersection, revealing a significant research gap. The review highlights how AI fosters both mechanistic dehumanization and animalistic dehumanization. The study further introduces hospitality-specific applications of emotional labor theory, demonstrating how emotionally expressive AI may lead to assimilation-induced dehumanization.
As a critical narrative review, this study did not follow a systematic review protocol. Article selection prioritized theoretical contribution and industry relevance, which may introduce selection bias and limit replicability. Findings should be interpreted in the context of a rapidly evolving research landscape. Nonetheless, the review follows best practices for critical synthesis and offers hospitality-specific insights that bridge psychology, ethics, and technology. It identifies research gaps around AI-driven emotional disconnection, cultural nuance, and power asymmetries. These findings encourage empirical validation and further theoretical development tailored to the hospitality industry’s service-intensive and emotionally charged environments.
This paper proposes hospitality-specific guidance, including hybrid AI–human HRM models and ethical oversight mechanisms, to mitigate risks associated with dehumanization. It also highlights the social implications of AI adoption, particularly its impact on employee dignity and psychological well-being, and emphasizes the need for proactive organizational strategies. Although not systematic, the review adheres to best practices and provides a theoretical foundation for future empirical research.
AI systems in hospitality risk normalizing dehumanizing practices that reduce workers to data profiles and suppress emotional individuality. This paper highlights how automation can unintentionally diminish human dignity, increase emotional detachment, and exacerbate exclusion, especially among culturally diverse or emotionally expressive employees. These dynamics have broader implications for identity, inclusion, and psychological safety in service organizations. The study calls for responsible AI design that recognizes the social complexity of hospitality work and reinforces human connection rather than undermining it. Failing to address these concerns may lead to long-term workforce disengagement and erosion of trust in AI-enabled environments.
This study presents one of the first applications of dehumanization theory and AI ethics to the hospitality sector, proposing a theoretical framework to support future empirical research and the ethical implementation of AI.
