In high-tempo operational environments deeply empowered by artificial intelligence (AI) technologies, the impact of strategic decision-making on campaign and tactical levels has become increasingly prominent. The Common Operational Picture (COP), constructed through multi-source sensor data fusion and advanced algorithmic technologies, provides a comprehensive domain awareness system, enabling commanders to devise more precise operational plans and achieve effective suppression of adversaries. The integration of AI-assisted analytical systems based on Large Language Model (LLM) has significantly enhanced the scientific rigor and effectiveness of operational decision-making. Meanwhile, breakthroughs in LLM have further expanded the capabilities of machine-assisted analysis, allowing it to play a greater role in battlefield situational awareness. This study innovatively combines COP with intelligent agents, proposing a COP-based framework for situational awareness agent applications. It thoroughly explores the potential of intelligent agents in the field of situational awareness, emphasizing their ability to automate data processing, optimize resource allocation, and support proactive decision-making. Additionally, the study offers a forward-looking perspective on future trends in situational awareness technologies. The proposed framework not only addresses current operational challenges but also lays the foundation for next-generation intelligent command and control systems, marking a significant step toward advanced AI-driven military capabilities.