Trusting the Machine : A Qualitative Study on HR Professionals' Trust in AI-Driven Recruitment in the Swedish Public Sector

Sammanfattning

In recent years, the use of Artificial Intelligence (AI) has increased across numerous sectors. In recruitment, this shift has transformed the landscape, shaped its practices and introduced new opportunities and challenges. AI can assist HR professionals in their recruitment process by streamlining efficiency and enhancing hiring processes. However, increased use of AI in recruitment can create challenges to be dealt with by human employees, including the need for oversight, regulation, and bias mitigation. These challenges become especially prevalent in the public sector due to bureaucratic constraints, political influences, and multiple stakeholders creating barriers that make structural and technological advancements difficult to implement. Consequently, this leaves HR professionals to navigate the new recruitment environment. While existing literature primarily focuses on the private sector or the broader global context, limited research exists on how HR professionals in the Swedish public sector perceive the integration of AI in the recruitment process. Therefore, the primary research purpose of this study was to explore and understand HR professionals’ trust in AI-driven recruitment in the Swedish Public sector. Furthermore, we sought to explore what specific factors converge to foster, shape, and influence HR professionals’ trust in AI, and if they lead to observable outcomes. This purpose was addressed through a qualitative and exploratory research design, collecting data through semi-structured interviews with HR professionals from two public sector organizations in Sweden. The empirical findings showed that HR professionals’ trust in AI-driven recruitment is not a linear process with a final step. Rather, it is a complex phenomenon with interaction between various factors. The results present trust as a continuous, evolving process, shaped by a feedback loop of experience and reflection. A conceptual framework was produced to present the results and illustrate how contextual factors shape HR professionals’ trust with influence from individual mediators, leading to a set of observable outcomes. Overarching systemic pressures that guide the process throughout were identified as dynamic tensions. Various barriers to trust and successful AI implementation were identified, including an existing knowledge gap, insufficient training, and a lack of system integration. Additionally, one’s individual propensity to trust in technology was a driving force behind trust in AI. The conclusions drawn from our research contribute to the ongoing theoretical, practical, social, and ethical debate. The findings offer insights into the topic of trust in AI-driven recruitment and further the existing literature and models on trust. Our conceptual framework can be used as a practical tool by various stakeholders, including HR professionals, managers, and organizations to better understand the factors that shape trust in AI-driven recruitment.