Artificial intelligence in the recruitment process. How can companies gain applicants’ trust?

This master’s thesis explores the role of artificial intelligence (AI) in modern recruitment processes with a particular focus on applicants’ trust. As digitalization and AI increasingly transform the world of work, organizations are adopting AI-supported recruiting tools to enhance efficiency, standardization, and data-driven decision-making. At the same time, the use of AI in personnel selection raises important questions regarding transparency, fairness, and acceptance from the applicants’ perspective.

The objective of this thesis is to examine how applicants perceive AI-assisted recruitment processes and which aspects are relevant for the development of trust in this context. To address this research objective, a qualitative research design was chosen. Semi-structured interviews were conducted with participants who had either experienced AI-supported recruitment processes or reflected on their expectations toward such processes.

The empirical data were analyzed using qualitative content analysis following Kuckartz’ approach. This method allows for a systematic examination of subjective perceptions, attitudes, and evaluations, while combining theory-driven and data-driven coding. The analysis focuses on applicants’ experiences with different forms of AI usage in recruitment, their expectations toward human and technological decision-making, and their assessment of AI-supported processes within the broader candidate journey.

By linking theoretical concepts of trust in technology with empirical insights from applicants, this thesis contributes to the growing body of literature on AI in recruiting. In addition, it provides a structured foundation for further academic research and offers valuable insights for organizations seeking to better understand applicant perspectives on AI-supported recruitment processes.