Technological advancements are rapidly transforming our operational environment, ushering in an era where autonomous systems and military artificial intelligence (AI) can not only sense, classify, and prioritize targets across complex battlespaces, but also generate strike recommendations and execute operations at speeds that outstrip human cognition and ethical-legal deliberation. In this machine-accelerated environment, the foundational safeguards of International Humanitarian Law (IHL)—distinction, proportionality, precaution, and accountability—are increasingly strained as human oversight becomes procedural rather than substantive. Consequently, AI-enabled targeting and autonomous weapons systems (AWS) pose a profound humanitarian risk because they compress decision cycles, blur civilian–combatant boundaries through data-based surveillance pipelines, institutionalize algorithmic casualty thresholds, and diffuse responsibility across opaque socio-technical systems. The capability of AIassisted systems to scale lethality faster than human review is sufficient to defeat traditional compliance practices. It also heightens risks of escalatory instability, widens accountability gaps, and normalizes software-mediated harm. Therefore, no state can afford to ignore the strategic and humanitarian threats posed by autonomous warfare. This article investigates how AI-enabled autonomy in targeting and command-and-control affects civilian protection, erodes humanitarian boundaries, and challenges the applicability and enforcement of IHL in contemporary conflicts. It aims to examine the emergence and operationalization of AWS and AI-assisted targeting within multistate warfare and urban combat, and their impacts on distinction, proportionality, and accountability within IHL-compliant targeting practice. Moreover, it analyses the mechanisms by which autonomy is generated and exercised and their implications for human control, legal review, and evidentiary traceability. Furthermore, it identifies technical, legal, and policy-based countermeasures that together are necessary to recentre human moral agency and preserve civilian protection in the age of AI-enabled warfare. Anchoring the analysis, comparative case studies of the Israel–Gaza conflict and the Russia–Ukraine war demonstrate the operational reality of these dynamics: largescale deployment of AI-assisted targeting platforms and machine-speed command systems compress decision cycles, repurpose civilian surveillance infrastructures for military targeting, elevate civilian harm through algorithmic misclassification and preset casualty thresholds, and exacerbate accountability gaps—thereby evidencing a structural, cross-contextual erosion of humanitarian protections in AI-enabled warfare. –Reproduced

https://www.istm.gov.in/library/information_bulletin/journal