Thesis Abstract

Abstract
The use of Artificial Intelligence (AI) in employee performance evaluation has gained significant attention in recent years, as organizations seek innovative ways to enhance their performance management processes. This thesis explores the application of AI technologies in evaluating employee performance and its impact on organizational outcomes. The study investigates the benefits, challenges, and implications of integrating AI into traditional performance evaluation systems, with a focus on improving objectivity, efficiency, and accuracy in assessing employee performance. Chapter One provides an introduction to the research topic, outlining the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of key terms. The chapter sets the foundation for understanding the significance of utilizing AI in employee performance evaluation and establishes the framework for the study. Chapter Two presents a comprehensive literature review on AI applications in performance management, covering ten key areas including the evolution of performance evaluation methods, the role of AI in enhancing objectivity, the impact on employee engagement and motivation, challenges associated with AI implementation, and best practices for integrating AI into performance evaluation processes. Chapter Three details the research methodology adopted in this study, encompassing various components such as research design, data collection methods, sampling techniques, data analysis procedures, ethical considerations, and limitations of the study. The chapter provides insights into the empirical approach used to investigate the use of AI in employee performance evaluation. Chapter Four presents a detailed discussion of the findings derived from the research, analyzing the effectiveness of AI technologies in enhancing employee performance evaluation practices. The chapter explores the implications of AI integration on performance appraisal accuracy, fairness, and overall organizational performance, highlighting key trends, challenges, and opportunities identified through the study. Chapter Five concludes the thesis by summarizing the key findings, implications, and recommendations for future research and practice. The chapter discusses the significance of leveraging AI in employee performance evaluation, identifies potential areas for further investigation, and offers practical insights for organizations looking to implement AI-driven performance management systems. In summary, this thesis contributes to the growing body of knowledge on the use of AI in employee performance evaluation, shedding light on the opportunities and challenges associated with adopting AI technologies in performance management processes. The research findings provide valuable insights for organizations seeking to enhance their performance evaluation practices through the integration of AI, ultimately driving improved organizational outcomes and employee performance.

Thesis Overview

The project titled "Use of Artificial Intelligence in Employee Performance Evaluation" aims to explore the application of artificial intelligence (AI) technologies in the realm of employee performance evaluation within organizations. With the increasing emphasis on data-driven decision-making and the need for more efficient and accurate performance assessment processes, AI presents a promising solution to enhance the traditional methods of evaluating employee performance. The research will delve into the various AI tools and techniques that can be leveraged for employee performance evaluation, such as machine learning algorithms, natural language processing, sentiment analysis, and predictive analytics. By harnessing these advanced technologies, organizations can potentially automate and streamline the performance appraisal process, leading to more objective, consistent, and real-time feedback for employees. Furthermore, the study will investigate the potential benefits and challenges associated with implementing AI in employee performance evaluation. It will examine how AI can help identify patterns, trends, and correlations in employee data to provide valuable insights for decision-making and talent management. Additionally, the research will address concerns related to privacy, bias, and ethical considerations that may arise when using AI for performance evaluation. The project will also explore case studies and best practices from organizations that have successfully integrated AI into their performance evaluation processes. By analyzing these real-world examples, the research aims to provide practical insights and recommendations for organizations looking to adopt AI technologies for enhancing their performance appraisal systems. Overall, the project on the "Use of Artificial Intelligence in Employee Performance Evaluation" seeks to contribute to the growing body of knowledge on the intersection of AI and human resource management. Through a comprehensive research overview, this study aims to shed light on the potential of AI to revolutionize employee performance evaluation practices and drive organizational performance and success in the digital age.