Artificial intelligence (AI) has emerged at the center of modern warfare, playing an operational support role in the recent U.S.-Israeli strike on Iran. Anthropic's Claude and Palantir's Gotham were used for intelligence assessments and target identification. Experts predict further expansion of AI in military applications.
In the massive joint U.S.-Israeli strikes on Iran, artificial intelligence (AI) functioned as an operational support layer that compressed the time between intelligence gathering and battlefield execution. According to U.S. media reports, the U.S. military used Anthropic’s AI model Claude for “intelligence assessments, target identification and simulating battle scenarios.” Palantir’s Gotham data platform played a key role in pinpointing key military facilities of Iran’s Islamic Revolutionary Guard Corps and its leadership hideouts. In practice, Gotham organized and summarized vast volumes of defense-related data from satellites, signals intelligence and other classified sources, while Claude supported commanders by comparing and analyzing different operational scenarios based on that information.
Kim Gi-il, professor of military studies at Sangji University, said, “The recent case shows that AI has become so central to modern warfare that it is no exaggeration to call this an ‘AI war.’” Choi Byoung-ho, a collaboration professor at Korea University’s Human-Inspired AI Research, noted that AI technology is likely to be adopted across the full spectrum of military operations, from intelligence analysis to direct combat. He added that Claude was most likely used primarily to analyze information, process and summarize data, and report up to the stage right before a decision is made.
Choi foresaw a future where, upon a human order, an agentic AI could draw up an operations plan on its own, select appropriate weapons, choose specific targets and carry out weapons deployment—what Anthropic appears to have rejected in this case. Technically, it is already possible, though error margins remain large, and the technology will eventually advance there.
For Korea, the U.S. case highlights structural gaps, with domestic defense companies arguing that standards defining “defense AI” remain ambiguous and access to sensitive military data is limited. The military seeks systems ready for immediate use, creating friction. Kim said, “(The military) tends to have little real understanding of the maturity of private sector technology or the constraints companies are facing, and that disconnect is creating serious friction. Expanding points of contact and closing that gap in speed and expectations is one of the biggest challenges for Korea’s defense AI today.”
The Iran strike previews choices Korea will face in building its own foundation models for defense. Choi said, “The fact that a foundation model was used in a war means it is really efficient. Thus, (Korea) will probably adapt its models to be used in war as well.” Experts warned that military adoption has outpaced global governance. Kim noted, “Military and ethical positions, values and even ideological perspectives are now colliding. There needs to be an international agreement, some kind of normative framework or protocol, governing the military use of defense AI, but at present, such standards are virtually nonexistent.” Choi added that preventing harm from foundation models by big tech in the U.S., China and elsewhere requires U.N.-style conventions, but Donald Trump’s dismantling of frameworks has left international solidarity absent.
