The preparation gap: IHL, human–machine teaming and assurance in military AI systems

Abstract Artificial Intelligence (AI) systems are increasingly supporting targeting, intelligence analysis and operational planning across military domains, reshaping how commanders use force through human–machine teaming (HMT). HMT offers operational advantages, but risks such as automation bias, adversarial manipulation and degraded performance pose challenges for the ability of deployers to use AI systems in compliance with international humanitarian law (IHL). This article argues that adherence to IHL cannot be deferred until hostilities arise; system design, testing, governance and training must be structured in advance to establish the conditions under which AI-enabled human–machine teams can exercise appropriate human judgement consistent with IHL obligations. The paper proposes an HMT Assurance Card, a cross-disciplinary life-cycle instrument integrating IHL obligations, civilian harm pattern analysis and AI governance frameworks into measurable standards applicable across the AI system life cycle, defence institutions and coalition environments.