EXPLORING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON RECRUITMENT FAIRNESS AND CANDIDATE EXPERIENCE IN LARGE COMPANIES

The paper primarily discusses how AI is gradually influencing the process of recruitment in terms of fairness and candidate experience in big companies through bibliometrics of 1,000 peer-reviewed articles indexed in Scopus and Web of Science. To perform the analysis, VOSviewer and Biblioshiny have been used to visualize and make graphical representations of the trends in published works, influential authors and journals, high-impact countries, and the fields thematic structure. The results reveal that since the year 2018 there has been a considerable increase in research activity which can be attributed to the growing introduction of AI-driven recruitment tools and to the rising anxieties regarding fairness, bias, transparency, and accountability. The highly cited works from 2016 to 2021 have created the intellectual core of the field and have been dealing with the topics like algorithmic discrimination, ethical governance, and socio-technical implications of AI. The keywords and bibliographic coupling point out four prominent thematic areas, namely, EQ and bias of algorithms, technical and methodological advancements, HRM and recruitment applications, and broader managerial or contextual themes. The field is dynamic in terms of growth but still, it is highly fragmented and there is next to no empirical research on how candidates view AI-mediated hiring. The study reveals essential issues related to candidate experience, cultural diversity, human-AI decision-making interactions, and governing procedures. The controversy, by uncovering the knowledge structure, not only gives a summarized view of ongoing studies but also reveals new topics and establishes future research paths that will facilitate the development of AI recruitment systems that are more transparent, equitable, and centered around humans.