Artificial intelligence(AI) is a well and indeed done deal, and now the AI economy is not only keeping itself alive but also being regarded as a force for transformation to transform fighting and its prediction and prevention into a global endeavor. Since it can use the power of massive data sources and machine learning and pattern recognition algorithms, AI systems can detect and warn of early signs of conflict so that decision-makers can get a head start. Much more specifically, an emphasis on data can amplify bias or produce incorrect predictions, undermining the trust in the results that AI promises to provide. There are significant ethical, political, and technical challenges to integrating AI into peacekeeping frameworks that need to be carefully walked along to use AI responsibly. It is this paper that studies those dimensions and looks to the future to analyze how AI might be distributed in conflict management.

The emerging US-China rivalry over Artificial Intelligence (AI) and cutting-edge technologies has become a fundamental aspect of contemporary global politics. This research explores how the mission for technological dominance between these two major powers is redesigning the geopolitical landscape, transforming long-standing coalitions, and introducing new frontiers of competition such as innovation, data manipulation, and semiconductor supply chains. The research explores critical developments such as the rise of strategic tech-driven coalitions like QUAD and AUKUS in setting global narratives around AI governance. This research applies the theoretical lens of Defensive Realism, which argues that states act to preserve their security in an anarchic international system by countering potential threats. This qualitative study examines how AI leadership and control over innovative technologies are becoming strategic instruments in the restructuring of geopolitical power dynamics.

The rapid integration of artificial intelligence (AI) in all domains of society is reshaping the academic landscape, calling for a change in curriculum design and delivery. This systematic review investigates how the educational system is changing to adapt its curriculum to align with the opportunities and challenges created by AI technologies. The four primary theoretical frameworks include Constructivist Learning Theory, Technological Pedagogical Content Knowledge (TPACK), Digital Capital Theory, and the 21st-Century Skills Framework in the framework of AI education teaching, technical and equity dimensions. The results show that when AI promises personal education, administrative performance, and modern teaching methods, there are important gaps in curriculum education, the preparation of teachers, and moral integration. In combination with current global literature, this study provides valuable insights for teachers, policymakers, and curriculum designers in the AI-powered world.