Adopting AI for HRM in the Malaysian hotel industry: a Delphi study

Purpose The Malaysian hotel industry, valued at US$4bn, faces persistent human resource management (HRM) challenges exacerbated by COVID-19-related disruptions. This study aims to identify and rank the factors influencing the adoption of artificial intelligence (AI) in HRM, particularly in addressing recruitment, retention, performance management and operational efficiency concerns. Design/methodology/approach A two-round modified Delphi method was used with 38 experts, including General Managers, human resources (HR) Directors and information technology (IT) Managers, from four- to five-star hotels in Penang, Malaysia. The first round elicited expert views on AI adoption in HRM, and the second round asked participants to rank the identified dimensions in order of importance. Thematic analysis and Kendall’s Coefficient of Concordance were used to analyze the consensus levels and priority rankings. Findings Seven key dimensions were identified: operational efficiency, workforce planning, performance management, employee retention and engagement, recruitment and talent acquisition, technological adaptation, customer service integration and compliance and legal challenges. Among these, operational efficiency and workforce planning ranked highest in importance, while compliance and legal challenges ranked lowest. Experts have highlighted AI’s role of AI in optimizing workforce planning, automating performance evaluations and improving employee engagement and retention. Originality/value This study is one of the first to examine AI adoption for HRM in the Malaysian hotel industry, offering novel insights into its implementation challenges and opportunities. The findings of this study provide a structured framework for AI integration in HRM, contributing to broader discourse on AI-driven workforce management in service industries.