Factors Affecting Employees’ Willingness to Accept Artificial Intelligence Technology

This research aims to explore the factors that affect employees’ willingness to accept artificial intelligence (AI) technology at work, guided by the Theory of Reasoned Action (TRA). A conceptual model was proposed to examine the direct effects of the four main antecedents – role clarity, extrinsic motivation, intrinsic motivation, and employee ability - on employees’ acceptance of AI technologies. The research also examined the moderating functions of trust in AI and perceived interactivity. The data were collected from questionnaires of the Egyptian hospitality industry participants and analyzed according to structural equation modeling. The findings show that role clarity, intrinsic and extrinsic motivation, and capability all have a significant and positive impact on AI acceptance by employees. Above all, trust in AI was a negative moderator of the relationship between role clarity and intrinsic motivation for adopting AI, wherein high levels of trust would inhibit employees' anticipation of clarity and motivation. Perceived interactivity did not play any vital moderating function. The findings contribute to literature in proposing the potential substitutive impact of trust in AI, and refuting hypotheses regarding interactivity as the prime driver of technology adoption. In practice, according to the research, there is a requirement to induce transparency, incentive and capacity among staff, and excessive dependence on AI systems may only provide subjective returns with diminishing benefits. The results from the study provide significant implications for hospitality managers interested in managing effective use of artificial intelligence technologies by promoting harmony of human-and-machine teamwork

CLARITY · Hospitality · Hospitality industry · Interactivity · Moderation · Structural equation modeling · Technology Acceptance Model · Theory of reasoned action · AI in Service Interactions · Ethics and Social Impacts of AI · Organizational and Employee Performance