present study sought to identify human resource educational management based on artificial intelligence. The researcher analyzed the results and findings of previous researchers using a systematic review and meta-synthesis approach and identified effective factors by performing the 7 steps of the Sandelowski and Barroso method. Of 277 articles, 25 were selected based on the CASP method. The validity of the analysis was also confirmed with a kappa coefficient of 0. 760. In this context, the kappa method was used to measure reliability and quality control, and its value was identified at the excellent agreement level for the identified indicators. The analyzing of the data collected in the ATLAS TI software resulted in the identification of 48 initial codes in 9 categories. Based on the meta-synthesis technique, 9 categories were also categorized as employee recruitment and selection, training and development, performance management, employee retention and satisfaction, talent management, strategic decision-making, employee experience, change management, and ethical and privacy issues. According to the results, AI-based HRM not only increases the efficiency and productivity of organizations but also creates new opportunities for skill development and workforce advancement by improving strategic decision-making in the field of HR. The use of AI technologies can make traditional HR processes such as recruitment, performance evaluation, and professional development smarter and more accurate, and allow organizations to respond more quickly to environmental changes. However, the successful implementation of this transformation requires culture building, employee training, and coordination between AI and human factors to fully benefit from this technology.