This study investigates the impact of artificial intelligence (AI)-driven recruitment on employees' trust, perceived fairness, job satisfaction, and turnover intention within five-star hotels. Using data collected from 350 hotel employees and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), the findings reveal that the use of AI in recruitment processes enhances perceived fairness and trust, promotes higher levels of satisfaction and organisational commitment, and reduces employees' intention to leave. The study further aims to examine the integration of AI technologies in human resource management (HRM) within the context of ethical governance and organisational performance in the luxury hospitality sector. Given that the tourism and hospitality industry is highly labour-intensive and dependent on human interaction, the ongoing digital transformation is reshaping its workforce requirements and service delivery models. The primary objective of this research is to explore the current state of AI-supported recruitment practices in five-star hotels, assess their effects on organisational efficiency, talent management, and employee experience, and discuss the balance between automation and human-centred values. Grounded in the Resource-Based View (RBV), Technology Acceptance Model (TAM), and Human Capital Theory (HCT), this study draws upon international academic research, industry reports, and empirical evidence. The results indicate that AI enhances recruitment speed, accuracy, and predictive capability while simultaneously introducing ethical challenges, perceived unfairness, and concerns over the loss of human touch. The study contributes to both theory and practice by proposing an integrated framework for the strategic, ethical, and human-centred use of AI in luxury hotel recruitment and talent management.
Mete Unal Girgen (Wed,) studied this question.