The Impact of Artificial Intelligence on Recruitment and Selection Processes in Human Resource Management

Thesis Abstract

Abstract
This thesis explores the impact of artificial intelligence (AI) on recruitment and selection processes within the field of Human Resource Management (HRM). The integration of AI technologies in HRM has transformed traditional practices, offering new opportunities and challenges for organizations. The study aims to investigate how AI is reshaping recruitment and selection processes, analyzing its implications on efficiency, fairness, and decision-making in HRM. The research begins by providing an overview of the background of AI in HRM, highlighting the rapid advancements in technology and the increasing adoption of AI tools by organizations. The problem statement addresses the potential risks and benefits associated with AI implementation in recruitment and selection, emphasizing the need for a comprehensive understanding of its impact. The objectives of the study include examining the effectiveness of AI in streamlining recruitment processes, evaluating its influence on diversity and bias in selection decisions, and identifying best practices for integrating AI tools in HRM. Through a thorough literature review, this thesis explores ten key themes related to AI in recruitment and selection, including the use of AI algorithms for resume screening, the impact of AI on candidate experience, and the ethical considerations of AI-driven decision-making. The research methodology section outlines the approach taken to investigate the research questions, including data collection methods, sample selection, and data analysis techniques. The study utilizes a mix of qualitative and quantitative research methods to provide a comprehensive understanding of the topic. The findings of the study reveal the multifaceted effects of AI on recruitment and selection processes, highlighting both advantages and challenges associated with AI implementation. The discussion of findings delves into the implications of AI on HRM practices, addressing issues such as algorithmic bias, data privacy concerns, and the role of human judgment in AI-driven decision-making. The study emphasizes the importance of ethical considerations and human oversight in leveraging AI technologies effectively in HRM. In conclusion, this thesis summarizes the key findings and insights gained from the research, offering recommendations for organizations looking to optimize their recruitment and selection processes through AI integration. The study underscores the need for a balanced approach that combines the efficiency of AI tools with human judgment and ethical considerations to ensure fair and effective HRM practices. Overall, this research contributes to the growing body of knowledge on the impact of AI on HRM and provides valuable insights for practitioners, scholars, and policymakers in the field.