AI systems used for military targeting are highly susceptible to GIGO (Garbage In, Garbage Out). The accidental strike on a school in Iran, caused by an outdated DIA database, demonstrates that even sophisticated AI can produce catastrophic results if the underlying data is not meticulously and continuously vetted by humans.

While the U.S. and China pursue hyperwar as a national strategy, its most rapid development is happening organically on the battlefield. Outnumbered forces like Ukraine are forced to innovate with autonomous systems out of necessity, driving a bottom-up adoption of hyperwar tactics.

In the Iran conflict, AI like Claude is finally solving the military's chronic problem of having more intelligence data than it can analyze. The AI processes vast sensor data in real-time to identify critical, time-sensitive targets like mobile missile launchers.

AI can optimize nuclear targeting by more efficiently identifying mobile targets and assessing battle damage. This increased efficiency could reduce the number of weapons needed for a specific objective, potentially alleviating pressure to massively expand the US arsenal and creating future arms control opportunities.

Instead of automating decisions, the Pentagon's AI strategy focuses on synthesizing vast amounts of data—assets, weather, potential reactions—to expand a human operator's situational awareness, enabling them to make better, more informed choices.

Defense tech firm Smack Technologies clarifies the objective is not to remove humans entirely. Instead, AI should handle low-value tasks to free up personnel for critical, high-value decisions. This framework, 'intelligent autonomy,' orchestrates manned and unmanned systems while keeping humans in the loop.

Contrary to the perception of AI in warfare as a future concept, Anthropic's Claude AI is already integral to U.S. military operations. It was actively used for intelligence assessment, target identification, and battle simulations in the recent Middle East air strikes.

Beyond offensive capabilities, the military sees AI as a tool for harm reduction. An LLM trained on visual data could act as a final check, flagging potential targets that show signs of civilian presence—like a playground outside a building—thereby augmenting human decision-making to prevent tragic errors.

In operations, AI models like Anthropic's Claude are used for intelligence analysis, summarizing media chatter, and running simulations to aid commanders. They are not used for autonomous targeting; any outputs go through layers of human review before influencing battlefield decisions.