This study examines how the AI-assisted social cognitive learning model can transform the nuances of political education learning by combining sociological and cybersocialization theories. This study is based on Bandura’s social cognitive theory and the idea of cybersocialization. This study proposes a model in which artificial intelligence (AI) is not only a source of information but also an interactive agent that helps students understand political issues, think critically, and shape their political identity. The research method used is a quantitative approach, including survey analysis and classroom observation focused on students engagement with AI tools, political simulations and peer discussions. The study population of 424 university students and 23 undergraduate students as samples were selected using purposive sampling techniques from Pancasila and Citizenship Education study programs in Indonesia who were exposed to and participated in AI-assisted learning activities such as simulations, debates, and reflective writing. The quantitative results show that students are highly engaged, politically informed, and cognitively activated, with an average score of 75.39 and a highly reliable instrument (α Cronbach = 0.974). These findings also indicate that political argumentation, empathy, and digital citizenship have all improved. This paper presents the AI-Enhanced Social Cognitive Loop (AISCL), a novel teaching method that uses AI as a sociotechnical partner in democratic learning. These results demonstrate that AI can help create immersive and culturally relevant civic education experiences that align with the needs of students growing up with internet technology.