AI-DRIVEN RECRUITMENT SYSTEMS AND THEIR TRANSFORMATIONAL IMPACT ON TALENT ACQUISITION PRACTICES IN THE BANGALORE IT INDUSTRY: A CONCEPTUAL FRAMEWORK FOR WORKFORCE AUTOMATION

• Pierre Dubois

  Department of Artificial Intelligence, University of Paris Institute of Technology, Paris, France

  Author

• Claire Moreau

  france

  Author

The rapid integration of artificial intelligence (AI) into recruitment systems is fundamentally reshaping talent acquisition practices, particularly within technology-intensive ecosystems such as the Bangalore IT industry. This study develops a conceptual framework to examine how AI-driven recruitment systems influence efficiency, fairness, decision transparency, and workforce automation outcomes. Drawing on algorithmic decision-making theory, talent datafication perspectives, and ethical AI governance literature, the paper synthesizes prior research to conceptualize the structural and behavioral transformation occurring in recruitment processes. AI-enabled systems, including automated resume screening, predictive analytics, and algorithmic candidate ranking, are increasingly replacing traditional human-centric hiring mechanisms. However, concerns regarding algorithmic bias, procedural justice, and transparency remain central to scholarly debates (Binns et al., 2018). The study integrates insights from human resource digitalization literature and emerging empirical evidence on applicant perceptions of AI fairness (Hosain et al., 2025) to construct a multi-dimensional framework consisting of technological, organizational, and ethical components. Findings suggest that while AI enhances recruitment efficiency and scalability, it simultaneously introduces governance challenges related to accountability and explainability. The paper contributes to theory by bridging HR analytics and algorithmic fairness literature, offering practical implications for IT organizations in Bangalore transitioning toward AI-enabled workforce systems.

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