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

Sunil Basnet *

Chief Human Resource Officer (iCHRO), Virtuosway, Kathmandu, Nepal.
 
Research Article
International Journal of Science and Research Archive, 2024, 11(01), 1111–1127.
Article DOI: 10.30574/ijsra.2024.11.1.0118
Publication history: 
Received on 28 November 2023; revised on 27 January 2024; accepted on 1 February 2024
 
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.
 
Keywords: 
Performance Management; Artificial Intelligence (AI); Machine Learning (ML); Algorithmic Evaluation; Human Resource Management
 
Full text article in PDF: 
 
Copyright information: 

Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0