Thesis Abstract

Abstract
The use of Artificial Intelligence (AI) in Human Resource Management (HRM) has gained significant attention in recent years due to its potential to revolutionize the recruitment and hiring processes. This thesis explores the application of AI for predictive hiring in HRM, focusing on how AI technologies can enhance the efficiency and effectiveness of talent acquisition. The research examines the current challenges in traditional hiring practices and proposes AI-driven solutions to improve the recruitment process and identify the best-fit candidates for organizational roles. 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 stage for the subsequent chapters by establishing the context and rationale for utilizing AI in predictive hiring. Chapter Two comprises a comprehensive literature review that examines existing studies, theories, and frameworks related to AI applications in HRM, predictive analytics, talent acquisition, and recruitment strategies. The review synthesizes key findings and identifies gaps in the literature to guide the research methodology. Chapter Three outlines the research methodology employed in this study, including the research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter details the steps taken to collect and analyze data to achieve the research objectives and address the research questions effectively. Chapter Four presents the findings of the research, highlighting the outcomes of applying AI for predictive hiring in HRM. The chapter discusses the effectiveness of AI algorithms in screening, shortlisting, and selecting candidates based on predefined criteria and job requirements. The results of the study provide insights into the impact of AI on improving recruitment outcomes and organizational performance. Chapter Five concludes the thesis by summarizing the research findings, discussing the implications of utilizing AI for predictive hiring in HRM, and offering recommendations for future research and practical applications. The chapter emphasizes the significance of incorporating AI technologies in HRM practices to enhance decision-making processes and optimize talent acquisition strategies. In conclusion, this thesis contributes to the evolving field of HRM by demonstrating the potential benefits of leveraging AI for predictive hiring. The research findings underscore the importance of embracing technological advancements to streamline recruitment processes, minimize biases, and identify top talent efficiently. By harnessing the power of AI, organizations can gain a competitive edge in attracting and retaining skilled employees, ultimately driving business success in the digital age.

Thesis Overview