This study was designed and conducted to develop an artificial intelligence-based agile marketing model for the pharmaceutical industry. The pharmaceutical industry, due to its regulated environment, product development cycles, diverse stakeholders, and competition, faces challenges in responding to changes. Under such conditions, marketing approaches are gradually losing their effectiveness, making the use of artificial intelligence necessary to enhance marketing agility and effectiveness. Although studies have examined agile marketing, artificial intelligence, and digital transformation in the healthcare sector, research integrating these concepts into a specialized model for the pharmaceutical industry remains limited. Therefore, this study was conducted to address this research gap. The research adopted a sequential mixed-methods approach and was carried out in two qualitative and quantitative phases. In the qualitative phase, data were collected through semi-structured interviews with pharmaceutical industry experts, marketing specialists, and artificial intelligence experts and analyzed using thematic analysis. In the quantitative phase, the proposed model was tested using a questionnaire administered to managers and experts of pharmaceutical and biotechnology companies. Confirmatory factor analysis and structural equation modeling using the partial least squares approach were employed to analyze the data. The qualitative findings led to the identification of eight dimensions: intelligent analysis of pharmaceutical market data, personalization of stakeholder interactions, agility in pharmaceutical marketing processes, intelligent marketing decision-making, compliance with pharmaceutical laws and regulations, product and service innovation management, pharmaceutical value chain integration, and development of digital marketing infrastructure. The quantitative findings confirmed the validity and reliability of the measurement model, and the structural relationships among the model dimensions were significant. Furthermore, importance analysis indicated that intelligent analysis of pharmaceutical market data and compliance with pharmaceutical laws and regulations were among the most important dimensions of the model, while the fit index confirmed the model’s quality. Overall, the findings indicate that artificial intelligence-based agile marketing in the pharmaceutical industry requires an integrated approach to technology, processes, human resources, organizational culture, regulations, and ethical considerations. The model can provide a framework for pharmaceutical companies to pursue digital transformation, increase marketing agility, improve decision-making, and enhance marketing performance.