Exploring the Acceptability of Artificial Intelligence in Human Resources Management: Insights From Swiss Organizations
Guillaume Revillod
Abstract
ABSTRACT This study looks at perceptions of artificial intelligence (AI) systems in human resources (HR) management within Swiss organizations. Based on a survey experiment provided to 324 private and public HR professionals, it explores how UTAUT's predictors—performance expectancy, effort expectancy, social influence and facilitating conditions—as well as top management support, the Private/Public dimension and control variables—age, gender, time with organization and hierarchical position—influence their acceptability of four different type of AI HR tools. To do this, this article is based on a multiple regression method. Its main findings are that, irrespective of the type of tool, performance expectancy, effort expectancy and social influence positively influence the acceptability of the HR AI tools studied, whereas working in a public organization has systematically a negative influence. This makes a significant contribution to the literature by offering valuable insights into how these factors collectively shape the willingness of HR professionals to embrace AI technologies in their practices. It also offers an overview of the levers that organizations aiming to adopt these AI tools could act upon.