FROM AUTOMATION TO RESPONSIBLE HIRING: A SYSTEMATIC REVIEW OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT AND SELECTION
DOI:
https://doi.org/10.69980/k10xhx82Keywords:
Artificial Intelligence, Recruitment, Personnel Selection, Algorithmic Hiring, Machine Learning, Applicant Reactions, Fairness, Trust, Explainable AI, Generative AI, Human-AI CollaborationAbstract
This study systematically analyses the growing body of literature that relates to artificial intelligence (AI) and its use in recruitment and selection. It aims to unify scattered evidence from human resource management, personnel psychology, information systems, business ethics, and computer science, and to identify key technologies, frameworks, methods, ethical issues, and future research directions. This paper examines the Scopus dataset consisting of 270 journals published in the English language, as well as a robust database of 125 studies based on the use of Artificial Intelligence in recruitment and selection. A detailed metadata analysis was carried out in order to identify the major trends in publishing, stages of recruitment, technologies, research methods, theories, and behavioural and ethical issues. The study area is on the rise, and 98 out of the 125 studies were published in the period from 2023. The most common technological features are algorithmic decision support, machine learning and résumé screening. The most dominant research themes that have been analysed in those studies are acceptance of the technology, bias/discrimination and efficiency/quality-of-hire. Fairness, trust, explainability, privacy, diversity, human–AI collaboration, and applicant reactions are among emerging concepts in the field. The literature review will have limitations arising from its reliance on abstracts and metadata alone, and given this, some details about the particular study may not be included. Future research should feature full-text review and formal quality measures in order to ensure a stronger evidence base. The study combines disparate evidence into the framework of responsible AI-driven recruitment and proposes a research agenda that emphasises fair audit, meaningful human governance, reproducibility of GenAI, timeline design, cross-cultural comparison, and post-hire validation.
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