Beyond Traditional Interviews: Inside the Minds of Recruiters

Abstract: The last years have presented a significant shift in human resource management processes, where measures based on traditional human interaction are increasingly replaced by digital and technological aids. In recent years, there has been a growing adoption of AI-interviews due to potential to streamline the hiring process, mitigate biases, and enhance the candidate experience. Historically, technological displacements have generated anxiety and concerns regarding the substitution of machines for labor. Nevertheless, as the role of machines continues to expand, greater attention is being placed on the significance of human-machine collaborations. However, the prospect of biases and discrimination in AI-interviews represents a potential obstacle to successful integration due to widespread concerns. Through a qualitative study, this thesis aims to answer how recruiters expect an integration of AI-interviews in the recruitment process. The sample includes 16 recruiters (including one pilot-interview). By analyzing the collected data through the lens of the theoretical framework, this thesis reveals that recruiters' expectations of AI-interviews are generally low. However, recruiters generally hold favorable expectations for the integration of other AI-tools into the recruitment process. The implications derived from this thesis therefore suggest that communication is critical in fostering balance and shared perspectives among internal stakeholders. To ensure successful integration and increase the expectations of recruiters, organizational support should also be customized to fit individual differences.