This study aimed to design a paradigmatic model for the application of artificial intelligence to enhance the export of Iranian electronic industry products. This applied qualitative study employed a grounded theory approach. Data were collected through semi-structured interviews with 16 experts, managers, and specialists in the electronic industry and smart technologies. Participants were selected using purposive sampling based on the principle of theoretical saturation. Interviews were transcribed verbatim, and data were analyzed using a three-stage coding process: open, axial, and selective coding. This approach enabled the identification of relationships among categories and the development of a comprehensive paradigmatic model. The analysis revealed that the application of artificial intelligence in the export of Iranian electronic products comprises five main dimensions: causal conditions, contextual conditions, intervening conditions, strategies, and outcomes. Causal conditions included global competitive pressure, changing demand patterns, and technological sanctions. Contextual conditions involved digital infrastructure, facilitating trade regulations, and international standards. Intervening conditions were identified as financial constraints, lack of specialized knowledge, and cultural resistance. Strategies encompassed data-driven market analysis, demand forecasting with AI algorithms, smart logistics optimization, digital marketing, and algorithmic decision-making. Outcomes included improved operational efficiency, enhanced decision accuracy, cost reduction, and sustainable competitive advantage in international markets. The proposed paradigmatic model clarifies the path toward digital transformation and intelligent decision-making in the export of electronic industry products in Iran. It provides a practical roadmap for exporters seeking to implement AI-driven strategies and optimize export performance effectively.