Algorithmic Bipolarity: A Neoclassical Realist Analysis of Military Artificial Intelligence Competition between the United States and China

This study considers artificial intelligence as a fundamental transformational dynamic that is restructuring the logic of production, organization of decision processes, and operational application of military capability in the international security environment. Advances in data processing, algorithmic analysis and real-time decision-making capabilities are leading to a redefinition of military effectiveness in terms of information superiority, system integration and decision speed. The study analyzes this transformation through the concept of algorithmic bipolarity. Algorithmic bipolarity refers to a distribution of power characterized by the concentration of data production, algorithmic innovation and computational capacity around two main techno-political centers, shaping the global artificial intelligence ecosystem in line with the institutional organizational logics of these centers. Structured within the framework of neoclassical realism, the analysis argues that systemically intensifying algorithmic competition drives great powers towards similar technological and military orientations, and that these pressures are processed through internal political and institutional structures in different models of capacity production. In this context, the study argues that convergence dynamics in the field of artificial intelligence produce common orientations, while divergence dynamics determine the institutional logic within which this capacity is produced. This process produces two distinct technopolitical models, conceptualized as Network-Based AI Governance in the case of the US and State-Centered AI Governance in the case of China. While the Network-Based model enables capacity generation within a distributed and multi-actor ecosystem, the State-Centric model offers an integrated structure based on centralized coordination and civil-military integration. Algorithmic bipolarity produces two distinct centers of gravity that influence the orientations of third states through these two technopolitical models. Technical standards, data governance practices, infrastructure architectures, hardware and infrastructure dependency, interoperability requirements and normative divergence produce frames of reference and channels of orientation for third states. These structural dynamics can shape third states’ defense planning, technology procurement choices, data governance models and digital infrastructure investments depending on their relationship with these prototypes. This study conceptualizes the role of artificial intelligence in international security through the relationship between the institutional structures that produce the capacity and the orientations that these structures generate.