Abstract



The aim of the present study is to validate the digital talent management model using artificial intelligence. The research method is applied in terms of its purpose and mixed (qualitative-quantitative) in terms of its implementation method. The statistical population of the qualitative part of the study includes 14 university professors in the field of public administration and managers and experts of mining companies who were selected by purposive sampling. The statistical population in the quantitative part includes active employees of mining companies, which was considered to be 215 people according to the Cochran formula and the sampling method is random. Data collection in the qualitative part was from semi-structured interviews based on theoretical foundations. The validity of the codes in the qualitative part was confirmed by two independent researchers and its reliability was confirmed by Cohen's Kappa index, and a questionnaire was used in the quantitative part. Content analysis was used to analyze the data in the qualitative part, and SPSS and Lisrel software were used in the quantitative part. As a result of this process, the identified dimensions of process functions included (automatic screening and decision support tools), job matching (accurate job and skills matching, improving qualitative assessments), personality trait assessment (psychological test analysis, personality type identification), educational recommendations (personalized education, smart and dynamic education, triple synergy and educational justice), and job turnover prediction (job turnover analysis system and preventive diagnosis). The results of confirmatory factor analysis also indicate the validity of the final conceptual model of the research.