HR EVOLUTION IN THE AGE OF AI: OPTIMIZING DECISION-MAKING WITH THE SALARY PREDICTION MODEL

Abstract

  Due to the integration of artificial intelligence, it's likely that current organizational frameworks and managerial processes will witness substantial changes. AI is radically reshaping traditional corporate setups and decision-making methodologies. The salary prediction model (SPM), which employs a backpropagation neural network (BPNN) rooted in AI technology, is refined using the Nesterov and Nadam techniques to boost its precision. This comprehensive model is recognized as the salary prediction model (SPM). The study's insights could greatly benefit HRM operations, reduce the workload for human resource professionals, and enhance overall job efficiency. Evaluations indicate that the Nadam optimization method exhibited superior performance and the swiftest convergence. The training lasted precisely 186 seconds, resulting in an anticipated accuracy score of 0.75%. The commendable learning capabilities and an accuracy rate of 79.4% achieved through the Nadam-enhanced BPNN-based SPM underscore its credibility. Such research findings could pave the way for future HRM solutions grounded in data mining.