AI-ML algorithm for enhanced performance management: A comprehensive framework using Backpropagation (BP) Algorithm

Abstract

In the era of economic globalization and heightened market competition, organizations face the imperative to establish robust performance evaluation mechanisms that drive both organizational development and individual employee motivation. This article delves into the multifaceted factors influencing employee performance, encompassing personal attributes, interpersonal relations, and work standards. The study takes a deep dive into the transformative integration of AI-ML algorithms, proposing a comprehensive framework for elevated performance management. Through the application of machine learning algorithms, this research seeks to revolutionize performance appraisals, impacting crucial HR processes such as employee selection, promotions, terminations, training initiatives, and remuneration adjustments. The investigation provides nuanced insights into the synergy between artificial intelligence, machine learning, and traditional performance evaluation methodologies, offering profound perspectives on contemporary organizational practices amid evolving challenges.