Counter-AI Operations

Definition

Counter-AI Operations is actions that detect, disrupt, deceive, or exploit adversary AI systems and data pipelines. In defense applications, it recognizes AI models, sensors, and MLOps as targetable operational systems. The hard part is escalation, attribution, and unpredictable second-order effects, especially when systems are deployed across contested links, coalition boundaries, and mixed human-machine teams. KhanBMS treats it as an emerging KhanBMS planning dimension alongside EW, cyber, and fires, tying the concept back to modular command, edge execution, and auditable authority.

Reference attributes

Layer

AI warfare mission area

Operational value

Recognizes AI models, sensors, and MLOps as targetable operational systems

Primary risk

Escalation, attribution, and unpredictable second-order effects

KhanBMS role

An emerging KhanBMS planning dimension alongside EW, cyber, and fires

Related terms

• Adversarial Machine Learning (AML)
  Study and defense of attacks that manipulate AI through crafted inputs, poisoned data, or model theft.
• Autonomous Cyber Defense
  AI systems that detect, triage, contain, and respond to cyber threats with bounded automation.
• AI Wargaming
  Use of AI agents and simulations to explore adversary moves, blue responses, and campaign dynamics.
• Electromagnetic Spectrum Operations (EMSO)
  Joint doctrine integrating electronic warfare and spectrum management as a single discipline.