Adoption of AI in Talent Acquisition: A Conceptual Framework

Abstract

Artificial intelligence has limited applicability in human resource management processes despite technological advancements. Talent acquisition is one of the crucial activities where the impact of AI is significantly conspicuous as compared to other HR processes. But implementing AI in this process requires effective adoption of the technology for ensuring operational efficiency. Moreover, there is a lack of conceptual clarity due to the limited scope of the study in this area. Hence, this study proposed a conceptual framework to help academicians and HR professionals adopt AI in talent acquisition and other allied areas of people management. This study reviewed three theories, the Value-based adoption model (V.A.M.), Technology-Organization-Environment (TOE), and the Task-technology fit (TTF) model, to identify the gap and propose a new framework. The traditional models were used in AI adoption, lacking a rational approach. Organizations should adopt Technology that provides maximum value to the organization compared with the costs and benefits. The study also proposed that the traditional TA methods organization and environmental-related factors and stickiness moderated between perceived value and adoption of AI in talent acquisition.