This study explores integrated IoT and Blockchain (BCT) technologies in the digital Human Resource Management (HRM) process, identifying the managerial phenomena. Using advanced algorithms like K-Means clustering, Random Forest predictive modeling, and Support Vector Machine sentiment analysis, the study convincingly shows that these technologies contribute to the optimization of HR management by picking the best method to use. The outcomes of the study reflect the successful segmentation of employees into clusters having strategies developed with the individual's specific needs in mind. The existing predictive models of the HRM strategies show an overall high accuracy level ranging from 86% to 92% precision. Sentiment analysis shows that the majority of the input from the employees (70%) is positive, which indicates their high job satisfaction. Also, the implementation of Blockchain technology ensures the security and reliability of the data, with a transaction rate of 200 transactions per second and an average block size of 2 MB. This demonstrates the ability of IoT and Blockchain technology to transform HRM practices which will aid in making decisions based on the available data, enhancing employees’ engagement, and ensuring the set of regulations is obeyed.