Thesis Abstract

Abstract
The utilization of Artificial Intelligence (AI) in Human Resource Management (HRM) has gained significant attention in recent years, particularly in the context of employee performance evaluation. This thesis explores the application of AI technologies for enhancing the process of evaluating employee performance within organizations. The study aims to investigate the potential benefits, challenges, and implications of incorporating AI-driven tools and systems in HRM practices to optimize performance evaluation processes. Chapter One 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 introduction sets the stage for understanding the importance of leveraging AI for employee performance evaluation in HRM. Chapter Two comprises a comprehensive literature review that examines existing studies, theories, and frameworks related to AI in HRM and employee performance evaluation. The review delves into various aspects such as the evolution of AI technologies, the role of AI in HRM, challenges and opportunities of AI implementation, and best practices for integrating AI in performance evaluation processes. Chapter Three outlines the research methodology adopted for this study, including research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter elucidates the approach taken to investigate the impact of AI on employee performance evaluation in HRM. Chapter Four presents a detailed discussion of the findings derived from the empirical research conducted in this study. The chapter analyzes the data collected and interprets the results to identify trends, patterns, and insights into the effectiveness of AI tools in enhancing employee performance evaluation practices. Chapter Five offers a conclusion and summary of the thesis, highlighting the key findings, implications, and recommendations for future research and practice. The chapter concludes by emphasizing the significance of leveraging AI for employee performance evaluation in HRM and the potential benefits it can bring to organizations. Overall, this thesis contributes to the growing body of knowledge on the application of AI in HRM, particularly in the context of employee performance evaluation. By exploring the opportunities and challenges of utilizing AI technologies, this study provides valuable insights for HR professionals, researchers, and policymakers seeking to enhance performance evaluation processes through technological innovation.

Thesis Overview

The project titled "Utilizing Artificial Intelligence for Employee Performance Evaluation in Human Resource Management" aims to explore the application of artificial intelligence (AI) in enhancing the process of evaluating employee performance within the realm of human resource management. As organizations strive to optimize their human capital and improve overall performance, the traditional methods of performance evaluation have shown limitations in terms of objectivity, efficiency, and effectiveness. By integrating AI technologies into this crucial HR function, it is anticipated that organizations can benefit from more accurate, data-driven insights that lead to informed decision-making and improved outcomes. The research will begin by providing an introduction to the topic, highlighting the significance of employee performance evaluation in HR management and the potential benefits of leveraging AI in this process. The background of the study will delve into the existing literature on performance evaluation methods, AI technologies, and their intersection in the context of HR practices. The problem statement will identify the challenges and gaps in traditional performance evaluation systems, emphasizing the need for a more advanced and reliable approach. The objectives of the study will be outlined to clarify the specific goals and outcomes that the research aims to achieve. These objectives may include evaluating the effectiveness of AI in enhancing performance evaluation accuracy, assessing the impact of AI on employee engagement and productivity, and identifying best practices for implementing AI-driven performance evaluation systems in organizations. The limitations of the study will be acknowledged to provide transparency about the constraints and boundaries within which the research is conducted. This may include constraints related to sample size, data availability, technological limitations, or other factors that may impact the generalizability of the findings. The scope of the study will define the specific parameters and focus areas that the research will cover, ensuring clarity on the extent of the investigation. The significance of the study will be discussed to highlight the potential contributions of the research to the field of HR management, AI applications, and organizational performance. By exploring innovative approaches to employee performance evaluation, the study aims to offer valuable insights and practical recommendations that can guide strategic decision-making in HR practices. The structure of the thesis will be outlined to provide a roadmap of the research framework, including the chapters, sub-sections, and flow of the study. This will help readers understand the organization of the research work and the progression of ideas from introduction to conclusion. Lastly, key terms and concepts relevant to the study will be defined to ensure clarity and consistency in the use of terminology throughout the thesis.