AI in Human Resource Management: Reimagining Talent Acquisition, Development, and Retention

人力资源管理 计算机科学 资源管理(计算) 知识管理 人力资源 管理 程序设计语言 经济
作者
Abdumalik Kadirov,Yulduzkhon Shakirova,Gulshodakhon Ismoilova,Nodirakhon Makhmudova
标识
DOI:10.1109/ickecs61492.2024.10617231
摘要

The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) heralds a transformative era for talent acquisition, development, and retention strategies. AI technologies, including Machine Learning (ML), Natural Language Processing (NLP), Robotics Process Automation (RPA), and Predictive Analytics, offer unprecedented opportunities to streamline HR processes, enhance decision-making, and improve overall organizational efficiency. This survey paper explores the multifaceted applications of AI within HRM, focusing on how these technologies are redefining traditional practices in talent management. In talent acquisition, AI-driven tools automate resume screening and facilitate sophisticated candidate search and engagement strategies, enabling a more efficient and effective recruitment process. For talent development, AI applications personalize learning experiences and optimize performance management, addressing individual needs and promoting skill advancement. Additionally, AI’s role in talent retention, through predictive turnover models and employee engagement platforms, underscores its potential to significantly lower turnover rates and foster a committed workforce. Despite these advancements, the paper also addresses the challenges and ethical considerations inherent in AI implementation, including algorithmic bias and privacy concerns. Through comparative analysis and illustrative graphs, this study provides a comprehensive overview of current trends and future directions in AI-enhanced HRM, offering valuable insights for practitioners and policymakers aiming to navigate the complexities of technology-driven human resource strategies.
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