AI collaboration and quality of work life: a dual perspective of hotel employees’ perceptions

Abstract

Purpose The growing prevalence of artificial intelligence (AI) integration in hotel services underscores the urgency of promptly analyzing hotel employees’ appraisals on AI collaboration. Drawing from the cognitive appraisal theory (CAT), we developed a dual-path model linking employee-AI collaboration with hotel employees’ quality of work life. This study aims to investigate the positive and negative evaluations of AI collaboration and the boundary role of employees’ perceived AI characteristics within this model. Design/methodology/approach Four studies – a pilot study (n = 101), a scenario experience (n = 265), a three-wave survey (n = 270) and a qualitative interview (n = 15) – were conducted to validate the theoretical model. Findings The results showed that psychological availability and expectation-disconfirmation mediated the relationship between employee-AI collaboration and quality of work life, respectively, along with emotional exhaustion. Perceived intelligence helps increase hotel employees’ psychological availability and decreases their expectation disconfirmation. Research limitations/implications This research reveals the double-edged sword effect of AI collaboration on individuals’ cognitive appraisals, deepening the understanding of AI-driven work processes in the hospitality industry. It calls upon managers to establish detection and intervention mechanisms, attend to AI’s limitations and provide resource support for employees. Originality/value This study provides theoretical insights into the employee evaluation process behind AI collaboration in the hotel industry and offers practical guidance for promoting harmonious human-AI interactions in hotel workplaces.