Effect of Artificial Intelligence on Employee’s Recruitment, Selection and Retention in the US Banking Sector: A Systematic Review
Description
In practice, process automation, machine learning, predictive analytics, generative AI, and AI-powered front-end tool chatbot are pioneer technologies of Artificial Intelligence (AI) used in recruitment, selection, and retention. However, concerns have been raised about its ability to support the process accurately without compromise/potential biases with manipulative datasets. This study aims to systematically review the existing empirical literature on the impact of Artificial Intelligence (AI) on recruitment, selection, and retention processes within Human Resource Management (HRM), specifically in the US banking sector. Through a systematic literature review, three research questions and hypotheses were formulated, and the study was guided by the PRISMA model, the study identified and analyzed empirical studies published between 2019 and 2024 that focused on AI-driven HR processes. The analysis revealed that AI is increasingly adopted in recruitment to automate candidate screening, improve efficiency, and reduce bias. However, the integration of AI into selection and retention processes is less advanced, with studies highlighting the need for human oversight to complement AI tools. The findings suggested that while AI enhances objectivity and efficiency in HRM, over-reliance on technology may overlook the nuanced judgments human recruiters provide. The study concludes with recommendations for further exploratory research and collaboration between banks and academic institutions to bridge existing knowledge gaps and optimize AI adoption in HR practices.
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