Purpose Artificial intelligence (AI) is reshaping recruitment by improving efficiency, scalability and perceived objectivity. Despite these advantages, AI-driven recruitment systems present ethical and governance challenges, including the risk of reinforcing historical biases and increasing workplace surveillance. This paper critically examines how algorithmic hiring affects recruitment outcomes, fairness and accountability. Design/methodology/approach A comprehensive review of scholarly literature, industry practices, and regulatory developments is conducted to assess the implications of AI in recruitment. The analysis considers the relevance of general governance frameworks, such as the EU AI Act, and evaluates their applicability to human resource (HR) contexts. Insights from human resource management, organisational behaviour and technology ethics inform an integrated assessment. Findings Existing AI regulations provide only indirect oversight of recruitment, failing to address the specific ethical risks of algorithmic hiring. The lack of mandatory mechanisms—such as bias audits, explainability requirements and candidate appeals—leaves AI-driven HR practices largely unregulated. This gap may exacerbate socio-economic inequities by reducing candidates to opaque algorithmic classifications. Targeted regulation and stronger corporate accountability are needed to align innovation with ethical standards. Practical implications Employers should adopt transparent AI recruitment practices, including explainable systems, third-party bias audits, and clear candidate redressal pathways. Policymakers are encouraged to extend regulatory frameworks to explicitly cover HR-specific AI applications, ensuring fair access and safeguarding employment rights. Originality/value This paper offers an interdisciplinary critique of AI hiring, bridging HRM, algorithmic ethics and regulatory policy. It contributes to responsible AI governance by advocating for sector-specific regulation to prevent exclusionary outcomes in labour markets.
Amlan Haque (2025) studied this question.