This article examines how integrating artificial intelligence (AI) into cruise missile systems, ballistic missiles, and ballistic missile defense (BMD) architectures reshapes deterrence mechanisms and escalation dynamics in regions characterized by persistent rivalry and compressed decision-making timelines, with particular emphasis on South Asia. Building on a typological-comparative approach, the analysis treats AI as a functional layer that reorganizes the sensor–processing–command–engagement chain across different missile technologies, rather than as an autonomous driver of strategic transformation. The study argues that AI-enabled applications—especially in sensor fusion, target discrimination, and decision support—tend to accelerate operational cycles while simultaneously increasing dependence on data integrity, software reliability, and network resilience. In regional contexts such as the India–Pakistan–China strategic triangle, these dynamics amplify existing dilemmas associated with dual-capable systems, counterforce incentives, and missile defense deployments, narrowing margins for error during crises. The findings suggest that technological advances associated with AI frequently coexist with heightened risks of misperception and inadvertent escalation, reinforcing long-standing concerns identified in the missile age while introducing new layers of vulnerability linked to cyber interference and algorithmic opacity. The article contributes to current debates on emerging technologies and strategic stability by situating AI within the structural conditions of regional deterrence and escalation management.
Marcos André Fortunato (Thu,) studied this question.