Beyond Algorithms: Artificial Intelligence in Recruitment as a Socio-Technical Phenomenon

Artificial Intelligence is transforming how organizations attract, assess and select talent. New screening, assessment and decision support tools are increasingly embedded in human resource processes, changing long-established roles, routines and decision-making processes. These technologies can deliver significant efficiency gains, but they also raise important concerns about fairness, transparency, accountability and the wider impact on applicants, employees and HR professionals. Research on artificial intelligence in recruitment has expanded rapidly in recent years but the literature still remains fragmented and is heavily skewed toward a technological perspective. Most studies focus on technical performance, predictive accuracy, and the potential for automation, while devoting considerably less attention to the human, organizational, and ethical dimensions of these systems. This paper addresses that gap through a systematic literature review and bibliometric analysis of thirty-nine highly cited and influential articles indexed in the Web of Science database that have been published between 2020 and 2025 by implementing a structured selection process of screening and analyzing relevant publications. The study is guided by three research questions: what are the dominant research themes in the field; which disciplines, countries, and journals have been most influential; and to what extent does the existing literature address human, organizational, and technological concerns? The results reveal a clear dominance of technical terminology, particularly with respect to artificial intelligence, machine learning and automation, while topics related to the workforce, organizational culture and changes in the distribution of power in decision-making are given much less attention. These results demonstrate a gap in the existing knowledge base and underline the need for a more sophisticated socio-technical outlook on artificial intelligence in human resource management. Moreover, the paper sketches the intellectual landscape of the field, identifying promising avenues for future research where the interaction between humans and AI is at the core of the scholarship on recruitment and selection.