Thesis Abstract

Abstract
The integration of artificial intelligence (AI) in various aspects of human resource management has revolutionized traditional recruitment and selection processes. This thesis explores the impact of AI on recruitment and selection processes in Human Resource Management (HRM) practices. The study aims to investigate how AI technologies such as machine learning, natural language processing, and data analytics have transformed the HRM landscape and reshaped the way organizations attract, assess, and select talent. 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 literature review in Chapter Two critically examines existing research on AI in recruitment and selection processes, identifying key themes, trends, and gaps in the literature. Chapter Three outlines the research methodology, including research design, data collection methods, sampling techniques, data analysis procedures, ethical considerations, and limitations of the research approach. The empirical findings are presented in Chapter Four, offering a detailed discussion of how AI technologies impact recruitment and selection practices, challenges faced by organizations, and potential implications for HRM professionals. The study concludes in Chapter Five with a summary of key findings, implications for practice, theoretical contributions, and recommendations for future research. Overall, this thesis contributes to the growing body of knowledge on the transformative role of AI in HRM practices, offering insights for organizations seeking to leverage AI technologies for effective recruitment and selection processes.

Thesis Overview

Research Overview: The integration of Artificial Intelligence (AI) in various sectors has significantly transformed traditional practices, and the field of Human Resource Management (HRM) is no exception. The project titled "The Impact of Artificial Intelligence on Recruitment and Selection Processes in Human Resource Management" aims to delve into the implications of AI adoption on the recruitment and selection functions within HRM. This research seeks to explore how AI technologies, such as machine learning algorithms and natural language processing, are revolutionizing the way organizations attract, assess, and hire talent. The utilization of AI in recruitment and selection processes has sparked debates regarding its effectiveness, efficiency, and ethical considerations. By examining the current landscape of AI applications in HRM, this study intends to provide insights into the benefits and challenges associated with AI-driven recruitment and selection methodologies. Furthermore, the research will investigate how AI technologies influence decision-making processes, candidate experience, and workforce diversity and inclusivity. Key areas of focus in this project include an analysis of the impact of AI on job matching, resume screening, candidate assessment, and predictive analytics in recruitment and selection activities. Additionally, the study will explore the potential biases and implications of AI algorithms in decision-making processes, as well as the role of HR professionals in overseeing and managing AI-driven recruitment strategies. Through a comprehensive literature review, empirical research methods, and data analysis techniques, this project aims to contribute to the existing body of knowledge on the intersection of AI and HRM practices. By critically examining the implications of AI on recruitment and selection processes, this research seeks to provide practical recommendations for organizations looking to leverage AI technologies effectively while addressing potential challenges and ethical considerations in the recruitment and selection domain. Ultimately, the findings of this study aspire to inform HR practitioners, policymakers, and academics on the evolving landscape of HRM practices in the era of AI integration.