The aim of this research was to design a future-oriented architecture model for cognitive warfare using qualitative content analysis and interviews with experts. This research was of a qualitative-applied type and qualitative content analysis method was used for data analysis. The expert community consisted of 9 experts from the fields of military, information technology, cybersecurity, and futures studies who were selected through purposeful selection. The data collection tool consisted of semi-structured interviews that were conducted through open-ended questions designed to extract 9 layers of cognitive warfare architecture. The results of the analysis showed that the cognitive warfare architecture is organized at three main levels: the central core includes the data collection and analysis layer; the middle rings include artificial intelligence and machine learning, human and cognitive interaction, drivers and trend analysis, and cybersecurity; and the outer ring includes systems coordination and integration, monitoring and feedback, strategic decision support, scenario building, and foresight. Each layer has specific components designed to support cognitive warfare capabilities, including data analysis, trend forecasting, cybersecurity management, and future scenario simulation. The model suggests that by integrating emerging technologies such as artificial intelligence and big data analytics into the cognitive warfare architecture, more effective decision-making, higher security, and greater adaptability can be achieved in the face of future challenges. The results of this research can contribute significantly to the development of national and military strategies in the field of cognitive warfare.