Thesis Abstract

Abstract
This thesis explores the application of Artificial Intelligence (AI) in revolutionizing the traditional approach to employee performance evaluation in Human Resource Management (HRM). The rapid advancements in AI technology have presented new opportunities for organizations to enhance their performance evaluation processes through automation, data analytics, and machine learning algorithms. This study investigates the potential benefits, challenges, and implications of utilizing AI in the context of employee performance evaluation. Chapter 1 provides an introduction to the research topic, presenting the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of key terms. The chapter sets the stage for exploring the role of AI in transforming HRM practices, specifically focusing on performance evaluation. Chapter 2 consists of a comprehensive literature review that examines existing research and theories related to AI, HRM, performance evaluation, and the intersection of these fields. The chapter covers ten key themes, including the evolution of AI in HRM, AI applications in performance evaluation, challenges of traditional evaluation methods, and best practices for implementing AI-driven evaluation systems. Chapter 3 outlines the research methodology employed in this study, detailing the research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter provides insights into how the research was conducted to address the research questions and achieve the study objectives. Chapter 4 presents a detailed discussion of the findings derived from the research, analyzing the impact of AI on employee performance evaluation in HRM. The chapter explores the effectiveness of AI algorithms in assessing and predicting employee performance, as well as the implications for HR professionals and organizational decision-making processes. Chapter 5 concludes the thesis by summarizing the key findings, discussing the implications of the research, and offering recommendations for future research and practical applications. The chapter also reflects on the significance of utilizing AI for employee performance evaluation in HRM and the potential benefits for organizations seeking to enhance their HR practices. Overall, this thesis contributes to the growing body of knowledge on the integration of AI technology in HRM, specifically focusing on its role in transforming employee performance evaluation processes. By exploring the opportunities and challenges associated with AI-driven evaluation systems, this study aims to provide valuable insights for academics, practitioners, and organizations looking to leverage AI for improving HRM practices.

Thesis Overview

The project titled "Utilizing Artificial Intelligence for Employee Performance Evaluation in Human Resource Management" aims to explore the integration of artificial intelligence (AI) technologies in the evaluation of employee performance within the realm of Human Resource Management (HRM). This research endeavor is motivated by the increasing need for innovative approaches to assess and optimize employee performance in organizations, coupled with the advancements in AI technologies that offer promising solutions in various domains. The research will delve into the current landscape of employee performance evaluation in HRM, highlighting the traditional methods, challenges, and limitations associated with manual appraisal processes. By incorporating AI techniques, such as machine learning algorithms and natural language processing, the study seeks to revolutionize the way performance assessments are conducted, providing more accurate, efficient, and data-driven insights into employee productivity, skills, and potential areas for improvement. The project will involve a comprehensive literature review to explore existing studies, frameworks, and tools related to AI applications in HRM and employee performance evaluation. This review will serve as the foundation for developing a research methodology that incorporates AI models tailored to the specific needs and objectives of employee performance assessment within organizations. The research methodology will encompass data collection strategies, AI model selection, implementation processes, and evaluation metrics to measure the effectiveness and impact of AI-based performance evaluation systems. By conducting empirical studies and case analyses, the project aims to demonstrate the feasibility and benefits of integrating AI technologies in HRM practices, particularly in enhancing the accuracy, objectivity, and timeliness of employee performance assessments. Furthermore, the findings and discussions derived from the empirical studies will provide valuable insights into the practical implications, challenges, and opportunities associated with deploying AI systems for employee performance evaluation. The project will address key issues such as data privacy, algorithm bias, employee acceptance, and organizational readiness in adopting AI-driven HRM solutions. In conclusion, this research endeavor on "Utilizing Artificial Intelligence for Employee Performance Evaluation in Human Resource Management" aspires to contribute to the growing body of knowledge on AI applications in HRM and provide actionable recommendations for organizations seeking to leverage technology for enhancing their performance evaluation practices. By embracing AI advancements in HRM, organizations can foster a culture of continuous improvement, talent development, and strategic decision-making, ultimately leading to a more productive and engaged workforce in the digital age.