Chapter 15: Ethical Integration of AI in HRM in IT Companies: Exploring Variables Through ISM and MICMAC Analysis

The emerging technologies comprising of robotics, machine learning, artificial intelligence (AI), etc., provided a bouquet of the opportunities which can transform the business. In the recent years, AI also finds its important application in the human resource management (HRM). The aim of the study is to determine the variables affecting the ethical use of AI in HRM. The variables influencing the ethical use of AI in HRM are identified and analysed using interpretative structural modelling (ISM). A hierarchical diagraph model was created for these variables, illustrating their relationships and influence. Additionally, MICMAC (Matrice d’ImpactsCroisés Multiplication Appliquée à un Classement) analysis was used to categorise the variables. The variables influencing the ethical use of AI in HRM are identified and analysed through the use of ISM. A hierarchical digraph model was created for these variables, illustrating their relationships and influence. Additionally, MICMAC analysis was used to categorise the variables. The study identified key ethical variables affecting AI integration in HRM, such as ethical AI deployment (EAD), data privacy and security (DPS), regulatory compliance (RC) and so on. MICMAC analysis discovered that EAD and AI literacy (AIL) are the independent factors, management commitment (MC) and impact on employment (IE), RC and DPS are mediating and performance management (PM) and AI transparency (AIT) are dependent variables. The findings of this study provide organisations with guidance on developing ethical AI strategies in HRM.