This study aimed to design and validate an artificial intelligence-based compensation system model in Iran’s Ministry of Sport and Youth. A sequential exploratory mixed-methods (qualitative-quantitative) design was employed. In the qualitative phase, 20 semi-structured interviews were conducted with qualified academic and executive experts; theoretical saturation was reached at interview 18 and two additional interviews were conducted to confirm category stability. Qualitative analysis followed three-stage coding, yielding 192 initial/open codes that were organized into 24 axial/subcategories and subsequently into 8 selective/main categories. In the quantitative phase, a researcher-developed 24-item questionnaire corresponding to the 24 axial categories was used. To compensate for nonresponse, 400 questionnaires were distributed across organizational strata, of which 365 complete questionnaires were retained for analysis. Quantitative data were analyzed using PLS-SEM, and the overall goodness-of-fit index was GOF=0.559. The final model comprises technological and infrastructural requirements, payment-system intelligence components, organizational justice-transparency-trust mechanisms, implementation challenges and barriers, legal-regulatory-ethical considerations, change-management and culture-building requirements, individual and behavioral employee outcomes, and macro-level strategic organizational achievements. The findings indicate that AI-based compensation is not merely a technological mechanism; its successful implementation requires coordinated technical, human, legal, ethical, and managerial arrangements.