This paper aims to explore the practical application of artificial intelligence (AI) technology in enterprise human resource management. By synthesizing the advantages and challenges of recruitment, training, performance evaluation, and employee satisfaction surveys, this paper summarizes the practical experiences of AI technology in enterprise human resource management. In terms of recruitment, natural language processing and machine learning can improve recruitment efficiency and quality. In training management, building a knowledge graph and applying natural language processing can help organizations classify and summarize knowledge and experience, thereby establishing a knowledge base or an intelligent Q&A system. For performance evaluation, automated assessment and measurement can enable enterprises to conduct efficient, consistent, and objective evaluations of large numbers of employees, greatly enhancing work efficiency and accuracy. Regarding employee satisfaction surveys, data mining algorithms and technologies can be applied to dig deeper into employees’ true needs and help enterprises improve employee satisfaction. However, AI technology also faces a series of challenges and issues in the application process, such as data security and privacy protection, technical rationality, and considerations for humanization. Through case analysis and practical guidance, this paper summarizes the lessons learned to avoid challenges and problems in the application of AI technology, which can help enterprises better utilize AI technology to promote long-term development and competitive advantages.