Implementing AI-Based Recruitment and Selection Processes in Human Resource Management

Thesis Abstract

Abstract
This thesis explores the implementation of AI-based recruitment and selection processes in the field of Human Resource Management. The use of Artificial Intelligence (AI) technologies has been gaining traction in various industries, and HRM is not an exception. The integration of AI in recruitment and selection processes is expected to streamline and enhance the efficiency and effectiveness of hiring practices. This research aims to investigate the benefits, challenges, and implications of incorporating AI technologies in HRM functions, specifically focusing on recruitment and selection. The study begins with an introduction that provides an overview of the research topic, followed by a background of the study that highlights the evolution of AI in HRM. The problem statement identifies the gaps and issues in traditional recruitment and selection methods, paving the way for the objectives of the study. The objectives include assessing the impact of AI on recruitment and selection processes, identifying the limitations and scope of AI integration, and understanding the significance of this technological advancement in HRM. A comprehensive literature review in Chapter Two explores existing studies, frameworks, and models related to AI in recruitment and selection. The review covers topics such as AI algorithms, machine learning, automation, and the role of AI in improving decision-making processes in HRM. The review also discusses the potential challenges and ethical considerations associated with AI implementation in HR practices. Chapter Three focuses on the research methodology, outlining the research design, data collection methods, sample selection, and data analysis techniques. The chapter also details the ethical considerations and limitations of the study, ensuring the validity and reliability of the research findings. The research methodology aims to provide a robust framework for investigating the impact of AI-based recruitment and selection processes in HRM. Chapter Four presents the findings of the study, analyzing the data collected from interviews, surveys, and case studies. The discussion delves into the benefits and challenges of implementing AI in recruitment and selection, highlighting the key insights and implications for HR professionals. The chapter also explores the role of AI in enhancing diversity, reducing bias, and improving the candidate experience in the recruitment process. Finally, Chapter Five concludes the thesis with a summary of the key findings, implications for practice, and recommendations for future research. The conclusion highlights the potential of AI technologies to transform HRM practices and underscores the need for HR professionals to adapt to the changing landscape of recruitment and selection. Overall, this thesis contributes to the growing body of knowledge on AI in HRM and provides valuable insights for organizations seeking to optimize their recruitment and selection processes through technological innovation.