Artificial intelligence, particularly generative AI, is changing how militaries around the world operate, from analyzing intelligence to managing logistics to making split-second decisions on the battlefield. But today’s AI doesn’t reason like a human or possess true contextual understanding. Even with techniques like retrieval-augmented generation (RAG), which improve access to relevant information, the model is still predicting likely responses based on statistical patterns, not actually comprehending meaning. As a result, it can produce incorrect, misleading, or overconfident answers, especially in ambiguous or high-stakes scenarios. Due to the nature of military operations, the DoD has released risk mitigation guidance to ensure that responsible statistical practices are combined with quality data to produce insightful analytics and metrics. In defense environments where the cost of a bad decision is measured in life, having a human in the loop, someone to guide, approve, or correct the AI is essential.
One important concept for safely and effectively using AI in military settings is human-in-the-loop, or HITL. This refers to designing AI systems so that people are actively involved in key steps of the decision-making process. Rather than giving AI full control, HITL ensures that trained operators can pause, review, and, if needed, override automated decisions. HITL is a foundational principle for agentic workflows, systems where AI agents are not merely executing isolated tasks, but interacting with humans in a coordinated, iterative loop. This collaboration enables more flexible, mission-aligned decision making while preserving human oversight. HITL is not just about ethics and risk, although those are essential factors. It is about quality, relevancy, and accuracy, providing human customer service and sales where needed and adding the qualities AI lacks, such as emotional intelligence, reasoning, advanced problem-solving and nuanced decision-making. It’s not just about safety, it’s about trust, accountability, and operational precision.
Autonomy Without Oversight = Risk
AI systems can process information and recommend actions faster than any human team. Yet speed without alignment creates risk. Autonomous agents can misinterpret ambiguous requests, select the wrong tools, or act on incomplete or misaligned data, especially in dynamic or adversarial conditions.
This isn’t a theoretical concern. In real-world operational environments, logistics planning, cybersecurity response, maintenance scheduling and missteps can degrade readiness or compromise missions.
HITL as an Operational Design Principle
HITL is often misunderstood as a failsafe or emergency brake for generative AI. It should be treated as a strategic control layer embedded into the system architecture from the beginning. Done properly, it enables systems to pause, ask for clarification, confirm intent, and hand control back to human operators when needed.
This allows commanders and analysts to stay in the loop, not just during initial training or after-the-fact audits, but at critical decision points in real time.
Two common patterns emerging in AI systems designed for defense operations:
- User Confirmation: the system requests operator approval before performing certain tasks. This works well for lower-risk actions like schedule updates or information retrieval.
- Return of Control: the AI recommends an action but lets the operator adjust or approve final execution. This is vital for higher-stakes tasks like system overrides, resource reallocation, or database changes.
Both models support operational collaboration and reduce the likelihood of costly AI misfires.
Making AI Mission-Integrated, Not Just Automated
In national defense, AI must be more than a tool that works on its own. It needs to be part of a team, meaning it’s reliable, explainable, and responsive to mission context. That requires building systems that:
- Connect to secure, verified data sources
- Operate within approved policy and cybersecurity boundaries
- Provide transparency and traceability across every step
- Allow human input at key moments, not just before or after a task
Without HITL, AI can become brittle, fast but fragile, unable to adapt to new information or shifting mission priorities.
Speed Meets Integrity and Accountability.
The Department of Defense doesn’t just need fast AI. It needs accountable AI, systems that can be trusted to support decision makers without replacing them. HITL ensures that autonomy doesn’t mean loss of control, and that technology enhances the mission rather than putting it at risk.
As the government continues to integrate AI across domains, from sustainment to cyber to warfighting, HITL must remain at the center of the design process. It’s not a constraint on innovation, it’s how we make AI effective, safe, and mission ready.
AI can act fast. But in the defense world, fast isn’t enough. It must act right, and that means keeping humans in the loop.
