The Impact of Artificial Intelligence on Recruitment and Selection

Artificial intelligence is reshaping the landscape of employee recruitment and selection in ways that are empirically documented, consequential, and deeply ambivalent. The evidence base reviewed in this paper confirms that AI tools deliver meaningful efficiency gains, particularly in high-volume screening and candidate engagement. It also confirms that the fairness implications of AI in recruitment are highly context-dependent, reflecting the quality of system design, training data, and governance arrangements rather than any inherent property of AI technology itself. The emerging consensus in the empirical literature points toward a model of augmented, rather than automated, recruitment: one in which AI tools extend the capabilities of human recruiters while final decision-making authority, moral responsibility, and contextual judgement remain with human actors. This model requires not only thoughtful technology design but also organisational investment in AI literacy, governance infrastructure, and accountability mechanisms. As the regulatory environment matures and AI capabilities continue to advance, the empirical research agenda on AI in recruitment will need to remain closely attentive to the evolving technical and institutional landscape. The stakes are high: recruitment decisions shape individual careers, organisational capabilities, and the broader structure of social opportunity. Ensuring that AI contributes constructively to these decisions, rather than encoding and amplifying historical injustice, is among the most important challenges facing HRM scholarship and practice in the years ahead.

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