The purpose of this study was to compare the performance of recruiters and an artificial intelligence (AI) program for processing internet employment big data in the enterprise resources planning (ERP) function. Previous AI implementations were discriminatory. Thus, the research question was: Could ERP staff perform better than AI in selecting the best candidate from internet employment real-time big data. A quasi-experiment was created using primary data. Job criteria were developed using machine learning to identify key skills from existing staff in a case study company. The skills were transformed into hiring criteria and a job description. AI software and a random sample of ERP recruiters assessed the same internet-based real-time big data. The results were compared between the ERP staff and AI using ANOVA followed by post-hoc Tukey. Contrary to the research question, AI out-performed ERP staff. The proposed approach might facilitate the research and development of big data, data analytics, artificial intelligence, and human resource management.