Thesis Abstract

Abstract
The integration of Artificial Intelligence (AI) technologies in recruitment and selection processes has gained significant attention in the field of Human Resource Management (HRM). This thesis explores the impact and implications of utilizing AI in enhancing recruitment and selection practices within organizations. The study aims to investigate how AI can streamline and optimize HR processes, specifically focusing on recruitment and selection procedures. 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 chapter sets the foundation for understanding the importance of incorporating AI in HRM practices, particularly in the context of recruitment and selection. Chapter Two consists of a comprehensive literature review that delves into existing research, theories, and studies related to AI in HRM, recruitment, and selection processes. This chapter provides insights into the current practices, trends, challenges, and opportunities associated with the integration of AI technologies in the HR domain. Chapter Three 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 aims to provide a transparent and systematic approach to conducting the research on utilizing AI in recruitment and selection processes. Chapter Four presents a detailed discussion of the research findings, interpretations, and implications derived from the data analysis. This chapter examines the impact of AI on recruitment and selection outcomes, as well as the benefits and challenges faced by organizations in implementing AI-driven HRM practices. Chapter Five concludes the thesis by summarizing the key findings, discussing the implications for HRM practitioners and researchers, and suggesting future research directions. The conclusion emphasizes the significance of leveraging AI technologies to enhance recruitment and selection processes in HRM, highlighting the potential for improved efficiency, accuracy, and fairness in talent acquisition. Overall, this thesis contributes to the growing body of knowledge on the application of AI in HRM, specifically focusing on recruitment and selection processes. By examining the opportunities and challenges associated with AI adoption in HR practices, this study aims to provide valuable insights for organizations seeking to leverage technology to optimize their HR functions and improve overall organizational performance.

Thesis Overview

The project titled "Utilizing Artificial Intelligence in Recruitment and Selection Processes in Human Resource Management" aims to explore the integration of artificial intelligence (AI) technologies in the traditional human resource management practices of recruitment and selection. This research seeks to investigate how AI can enhance and streamline these processes to improve efficiency, accuracy, and overall effectiveness in talent acquisition. The introduction of AI in recruitment and selection processes has the potential to revolutionize the way organizations identify and attract top talent. By leveraging AI algorithms and machine learning capabilities, HR professionals can automate various tasks such as resume screening, candidate sourcing, and pre-employment assessments. This can help in reducing manual workload, minimizing bias, and speeding up the recruitment cycle. The background of the study will delve into the evolution of AI technologies and their increasing relevance in the field of human resource management. It will also highlight the current challenges faced by organizations in the recruitment and selection processes, such as time-consuming manual screening, unconscious bias, and high costs associated with traditional methods. The problem statement will address the inefficiencies and limitations of conventional recruitment and selection practices, underscoring the need for innovative solutions like AI to address these challenges effectively. The research objectives will focus on examining how AI can optimize recruitment and selection processes, enhance candidate experience, and improve decision-making in talent acquisition. The study will also outline the limitations and scope of the research, acknowledging potential constraints such as data privacy concerns, technological barriers, and organizational readiness for AI adoption. The significance of the study lies in its potential to contribute valuable insights to HR practitioners, policymakers, and researchers on the benefits and implications of integrating AI in recruitment and selection practices. The research methodology will involve a comprehensive review of existing literature on AI in HR, case studies of organizations that have successfully implemented AI in recruitment, and primary data collection through surveys or interviews with HR professionals and AI experts. The findings chapter will present a detailed analysis of the data collected, discussing the impact of AI on recruitment metrics, candidate experience, and organizational performance. In conclusion, this project will provide a holistic overview of the opportunities and challenges associated with utilizing AI in recruitment and selection processes in human resource management. By exploring the potential benefits and risks of AI adoption, this research aims to offer practical recommendations for organizations looking to leverage AI technologies to enhance their talent acquisition strategies.