The present study aimed to propose a model for the application of artificial intelligence (AI) in private organizations influenced by human resource management, considering its antecedents and consequences. The research method was applied in terms of purpose and exploratory mixed-method (qualitative-quantitative) in terms of data collection. The statistical population of the study consisted of three sections: scientific documents, the qualitative section (experts), and the quantitative section (human resource managers of private organizations and companies in Tehran). The sample size in the qualitative section included 19 experts, who were selected using the principle of saturation and purposive non-random sampling. Additionally, in the quantitative section, 252 managers were selected through convenience sampling. In the qualitative phase, semi-structured interviews were used to collect data, and in the quantitative phase, a researcher-made questionnaire derived from the qualitative section was employed. In the qualitative section, validity was calculated through expert opinions, and reliability was assessed using inter-rater agreement and agreement between two coders, with the results indicating the validity and reliability of the qualitative data. Moreover, in order to determine the validity of the questionnaire, content and construct validity were utilized, and to assess reliability, Cronbach's alpha coefficient and composite reliability were employed, with the results indicating the validity and reliability of the tool. Data analysis in the qualitative section was conducted using thematic analysis with Maxqda 2022 software, and in the quantitative section, based on the research questions, descriptive and inferential statistical methods (one-sample t-test and confirmatory factor analysis) were applied using SPSS v23 and Smart PLS v8 software. The research findings indicated that the antecedents of AI application in human resource management include organizational strategy and vision, organizational culture, and resources and infrastructure. The consequences of AI application include improvement in the recruitment process, development of training, reduction of errors, increased accuracy, and the creation of competitive advantage. Furthermore, based on the identified antecedents and consequences, the research model was designed and demonstrated appropriate validity.