Understanding AI implementation in HR: a multimethod study in India's IT sector

Abstract

Purpose This study aims to explore the drivers of artificial intelligence (AI) implementation in human resource (HR) processes from the dual perspective of senior HR professionals (thought leaders who decide implementation), and middle- and lower-level HR professionals (agents who carry out implementation). Design/methodology/approach Using a multi-method approach, we conducted two studies in the Indian information technology (IT) sector. In qualitative Study 1, interviews with 11 senior HR professionals were conducted to gauge their perspectives on AI implementation. For quantitative Study 2, we used the dimensions from study 1 to craft the conceptual framework using the theoretical lens of unified theory of acceptance and use of technology (UTAUT). Survey data of 200 middle and lower-level HR professionals were analyzed using structural equation modelling and PROCESS macro. Findings Using Gioia’s methodology, we found five aggregate dimensions influencing AI-HR implementation: performance gains, usability, organizational support, attitude, and intention to use. In Study 2, performance gains significantly predicted HR professionals’ intention to use AI, while usability did not. Attitude served as a significant mediator, linking both performance gains and usability to intention to use. Organizational support emerged as a critical boundary condition that moderated the mediation effect (usability-attitude-intention), such that higher organizational support strengthened HR professionals’ positive attitudes towards AI. Practical implications Firms should enhance organizational support and develop mechanisms to foster AI–human collaboration. Originality/value This study uses a multi-method approach by taking the dual perspectives of senior HR professionals and middle and lower-level HR professionals in an underrepresented country context India.