Applicability, Challenges and Barriers to the Implementation of Artificial Intelligence in Human Resource Management: A Multiple Moderation Model

Abstract

Understanding the factors that influence the future intention to use Artificial Intelligence (AI) in Human Resource Management (HRM) is essential to promote the effective adoption of these technologies in organisational settings. Based on a multiple moderation model, this study examined the role of perceived applicability of AI in HRM and the moderating effect of implementation challenges and barriers on future usage intention. A mixed-methods research design was adopted. In the first phase, interviews were conducted with 11 Human Resources (HR) professionals with experience in digital transformation processes. The qualitative analysis identified key thematic categories that informed the development of the survey questionnaire. In the second phase – a quantitative study – 157 questionnaires were administered to employees working with AI tools in HRM contexts. Statistical analysis revealed a direct and significant effect of the perceived applicability of AI on future usage intention. Additionally, the results indicated that perceived challenges positively moderate this relationship, strengthening the impact of applicability as implementation contexts become more demanding. In contrast, implementation barriers did not exhibit a significant moderating effect. These findings suggest that AI acceptance in HRM is more influenced by operational and strategic challenges than by structural barriers. It is concluded that recognising the applicability of AI, together with the organisational capacity to address internal challenges, is a key factor in professionals' predisposition to adopt such technologies in the future.