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The rapid evolution of Human Resource (HR) systems calls for a more automated, secure, and efficient approach to manage employee data and decision-making processes. Traditional HR systems, often dependent on manual processes and legacy software, struggle with issues related to data security, scalability, and prediction accuracy. To address these challenges, this paper proposes an AI and blockchainbased HR management system that integrates machine learning models for employee retention, performance prediction, and smart contracts for secure record-keeping. The proposed system outperforms baseline models such as Logistic Regression and Decision Trees in key performance metrics, with accuracy of 9 2 %, precision of 9 3 %, recall of 90 %, F1-Score of 91 %, and AUC-ROC of 0.95. proposed research presents a clear advantage over existing systems by offering enhanced decisionmaking capabilities, improved data security, and transparent operations. The integration of blockchain ensures the integrity of employee records, while AI models predict HR outcomes with higher precision. This work contributes to the field by advancing automation and security in HR systems, providing significant value to both organizations and employees.
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Singh et al. (2025) studied this question.
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