Thesis Abstract

Abstract
The integration of Artificial Intelligence (AI) technologies in Human Resource Management (HRM) has revolutionized traditional recruitment and selection processes, enhancing efficiency, accuracy, and objectivity. This thesis explores the utilization of AI for recruitment and selection in HRM and aims to investigate its impact on organizational practices and outcomes. The study delves into the background of AI technology, its applications in HRM, and the potential benefits and challenges associated with its implementation. The research problem revolves around the need for organizations to optimize their recruitment and selection processes to identify and attract top talent in a competitive job market. The objectives of this study include examining how AI can streamline recruitment processes, improve candidate assessment accuracy, and enhance overall HR decision-making. The limitations of the study encompass the availability of AI technology, organizational readiness for AI adoption, and potential ethical implications. The scope of the study focuses on exploring AI applications in recruitment and selection across various industries and organizational sizes. The significance of this research lies in its potential to provide insights into the transformative impact of AI on HRM practices and its implications for organizational success. The structure of the thesis comprises an introduction, literature review, research methodology, discussion of findings, and conclusion. In the literature review, ten key areas related to AI in recruitment and selection will be examined, including AI algorithms, predictive analytics, bias mitigation, and candidate experience enhancement. The research methodology section outlines the research design, data collection methods, sample selection criteria, and data analysis techniques utilized in this study. The discussion of findings chapter presents the empirical results and their implications for HRM practices, organizational performance, and future research directions. Overall, this thesis contributes to the growing body of knowledge on AI applications in HRM and provides practical recommendations for organizations looking to leverage AI for recruitment and selection. By shedding light on the benefits and challenges of AI adoption in HRM, this research aims to inform strategic decision-making and enhance HR practices in the digital era.

Thesis Overview

Overview: The project titled "Utilizing Artificial Intelligence for Recruitment and Selection in Human Resource Management" aims to explore the integration of artificial intelligence (AI) technologies into the recruitment and selection processes within the field of human resource management. As organizations strive to enhance their talent acquisition strategies and streamline their hiring processes, the adoption of AI tools presents a promising solution to improve efficiency, accuracy, and objectivity in identifying and selecting the most suitable candidates for various job roles. Chapter One of the project provides a comprehensive introduction to the research topic, highlighting the background of the study, the problem statement, research objectives, limitations, scope, significance, the structure of the thesis, and the definition of key terms related to AI, recruitment, and selection processes in HRM. Chapter Two delves into an extensive literature review, examining existing studies, theories, and frameworks related to the use of AI in recruitment and selection. The review covers topics such as the evolution of AI technologies, the impact of AI on HRM practices, the benefits and challenges of AI adoption, and best practices for implementing AI tools in talent acquisition processes. In Chapter Three, the research methodology is outlined, detailing the research design, data collection methods, sampling techniques, and data analysis procedures employed in the study. The chapter also discusses the ethical considerations and potential biases associated with using AI-based systems in recruitment and selection. Chapter Four presents a thorough discussion of the research findings, analyzing the effectiveness of AI technologies in improving recruitment and selection outcomes. The chapter explores the key findings, identifies patterns and trends in the data, and discusses implications for HRM practices and future research directions. Finally, Chapter Five offers a comprehensive conclusion and summary of the project thesis, summarizing the key findings, discussing their implications for practice, and providing recommendations for organizations looking to leverage AI for recruitment and selection processes. The chapter also highlights the limitations of the study and suggests areas for further research to enhance the understanding and application of AI in HRM practices. Overall, this project aims to contribute to the growing body of knowledge on the integration of AI in human resource management, offering insights and recommendations to help organizations optimize their recruitment and selection processes through the strategic use of artificial intelligence technologies.