Thesis Abstract

Abstract
This thesis explores the application of artificial intelligence (AI) in the field of human resource management, specifically focusing on employee performance evaluation. The utilization of AI technologies for performance evaluation has gained significant attention in recent years due to its potential to enhance objectivity, accuracy, and efficiency in the evaluation process. This research aims to investigate the effectiveness of AI-based performance evaluation systems in improving the overall performance management practices within organizations. The study begins with an introduction to the topic, providing a background of the research area and highlighting the significance of utilizing AI in human resource management. The problem statement identifies the challenges and limitations associated with traditional performance evaluation methods, underscoring the need for innovative solutions such as AI technologies. The objectives of the study include assessing the impact of AI on performance evaluation outcomes, identifying key success factors for implementing AI systems, and examining the perceptions of employees and managers towards AI-driven performance evaluation. The research methodology section outlines the approach taken to conduct the study, including the research design, data collection methods, and data analysis techniques. A comprehensive literature review is presented, discussing existing studies and theories related to AI in performance evaluation, as well as exploring the potential benefits and challenges of implementing AI technologies in HR practices. The findings of the study reveal that AI-based performance evaluation systems offer several advantages, such as increased objectivity, real-time feedback, and data-driven insights. However, challenges related to data privacy, algorithm bias, and employee acceptance need to be addressed for successful implementation. The discussion of findings delves into the implications of these results for HR practitioners and provides recommendations for organizations looking to adopt AI in performance evaluation processes. In conclusion, this thesis underscores the potential of AI to transform traditional performance evaluation practices in human resource management. By leveraging AI technologies, organizations can enhance the accuracy and fairness of performance assessments, leading to improved employee engagement, motivation, and overall organizational performance. The findings of this study contribute to the growing body of knowledge on AI applications in HRM and offer practical insights for organizations seeking to embrace digital transformation in their HR practices.

Thesis Overview

The project titled "Utilizing Artificial Intelligence for Employee Performance Evaluation in Human Resource Management" aims to investigate the potential benefits and challenges of incorporating artificial intelligence (AI) in the evaluation of employee performance within the realm of human resource management. This research is motivated by the increasing interest in leveraging AI technologies to enhance HR processes and decision-making, particularly in the area of performance evaluation, which plays a crucial role in organizational success and employee development. The study will commence with a comprehensive introduction that sets the context for the research, followed by an exploration of the background of the study to establish the current state of employee performance evaluation in HR management. The identification of key issues and challenges in existing performance evaluation methods will lead to a clear articulation of the research problem and the specific objectives that guide this investigation. In recognizing the inherent limitations of the study, such as constraints in data availability or technological resources, the research will delineate the boundaries within which the investigation will be conducted, defining the scope of the study. Moreover, the significance of the research will be underscored, emphasizing the potential contributions and implications of integrating AI into performance evaluation practices in HR management. The structure of the thesis will be outlined to provide a roadmap for the reader, highlighting the organization of chapters and the flow of the research work. Additionally, key terms and concepts relevant to the study will be defined to ensure clarity and understanding of the terminology used throughout the thesis. The literature review section will delve into existing research and theoretical frameworks related to AI applications in HR management and employee performance evaluation. By synthesizing and analyzing relevant literature, this chapter aims to provide a solid foundation for the research, identify gaps in current knowledge, and inform the development of research hypotheses. The research methodology chapter will detail the approach, methods, and tools employed in the study, including data collection techniques, sample selection, and data analysis procedures. This section will elucidate the rationale behind the chosen research design and methodology, ensuring the reliability and validity of the study findings. Chapter four will be dedicated to the discussion of research findings, presenting and interpreting the results of the analysis conducted on the data collected. Through a systematic examination of the data, the study aims to draw meaningful conclusions, identify patterns or trends in employee performance evaluation with AI, and discuss the implications of the findings for HR practice. Finally, chapter five will encapsulate the conclusion and summary of the research, highlighting the key insights, contributions, and recommendations arising from the study. This concluding chapter will also reflect on the research objectives, discuss the implications of the findings for theory and practice, and suggest avenues for future research in the dynamic field of AI applications in HR management and performance evaluation.