# AI warfare

AI warfare is the use of artificial intelligence technologies to automate military operations and enhance or bypass human decision-making in armed conflicts, including intelligence analysis, targeting, and damage assessment.

AI warfare refers to the use of artificial intelligence technologies to automate military operations and enhance or bypass human decision-making in armed conflicts. AI systems are employed to rapidly analyze large volumes of military intelligence data, including making recommendations or decisions on who and what to target. This application of [artificial intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) has become increasingly prominent in recent conflicts, raising significant ethical, legal, and operational questions.

The integration of AI into warfare spans a range of functions, from intelligence processing and target selection to autonomous drone operations and damage assessment. While the concept has been discussed for decades, its practical implementation has accelerated since the early 2020s, driven by advances in [machine learning](https://www.wikiprompt.org/wiki/machine-learning), [deep learning](https://www.wikiprompt.org/wiki/deep-learning), and [large language models](https://www.wikiprompt.org/wiki/large-language-model). The first acknowledged civilian killed by an AI-assisted airstrike was Abdul-Rahman al-Rawi, a 20-year-old student, in a U.S. strike in Iraq in 2024. In 2026, the United States declared it would become an 'AI-first' warfighting force.

## Historical Development

### Russo-Ukrainian War (2022–present)

Following Russia's full-scale invasion in 2022, Ukraine launched a project with Palantir called Brave1 Dataroom to build AI systems using extensive combat data gathered throughout the war. The country developed tools for in-depth airstrike analysis, introduced AI to process large volumes of intelligence, and incorporated these technologies into the planning of long-range strike operations. These efforts aimed to counter Russian advantages in manpower and firepower by leveraging data-driven decision-making.

### Gaza War (2023–present)

As part of the Gaza war, the Israel Defense Forces (IDF) used artificial intelligence to rapidly and automatically perform much of the process of determining what to bomb in the Gaza Strip. The IDF's Unit 8200 developed AI systems, dubbed the Gospel and Lavender, to find targets for the Israeli Air Force. The Gospel automatically provides targeting recommendations to human analysts, who decide whether to approve strikes. Lavender identified 37,000 Hamas-linked individuals early in the war and was used alongside the Gospel, which chooses buildings or structures as targets.

According to a report by +972 Magazine and Local Call, strikes assisted by Lavender were routinely permitted to kill 5–20 civilians for each suspected Hamas militant, who were often bombed at home with their families. The IDF denies these claims, maintaining that every strike is assessed to minimize collateral damage and that there is no policy "to kill tens of thousands of people in their homes." Israel also deployed AI for audio analysis, facial recognition, and airstrike targeting. One such system helped identify the location of Hamas commander Ibrahim Biari through phone call analysis, leading to strikes that killed him as well as more than 125 civilians.

### 2026 Iran War

The 2026 Iran war has been described as the "first AI war," although the United States and Israel had previously used AI to identify targets in conflicts in the Middle East and the Gaza war, respectively. The U.S. used AI tools for military intelligence, targeting, and damage assessment in the war in Iran. Using the Maven Smart System, the U.S. attacked 1,000 targets in the first 24 hours of the war and 5,000 targets over the course of 10 days. The Pentagon revealed that Elon Musk's [Grok AI](https://www.wikiprompt.org/wiki/grok) tool was in use within Project Maven. While the U.S. had used Maven in 2022 to share targeting information with Ukraine and strike against Iraq, Syria, and the Houthis in 2024, Iran's attacks were its biggest.

Authorities investigated whether artificial intelligence was involved in an airstrike on an Iranian school that killed 170 civilians, the majority of whom were children. The United States Central Command emphasized that humans were making final targeting decisions. Per a White House tally released on April 8, the U.S. military hit over 13,000 targets in Iran during the war's first 38 days, including more than 2,000 command-and-control sites, 1,500 air defense targets, and 1,450 industrial infrastructure targets.

In spring of 2026, a USSOCOM intelligence report written in part with AI erroneously claimed that a Chinese ship in the region was transporting materials for a nuclear weapons program. A planned maritime interdiction operation got as far as having planes in the air before further investigation found the report to be inaccurate.

## Involved Companies

The Maven Smart System is developed by Palantir. It integrates [Anthropic](https://www.wikiprompt.org/wiki/anthropic)'s [Claude](https://www.wikiprompt.org/wiki/claude) as its large language model and uses [Amazon Web Services](https://www.wikiprompt.org/wiki/amazon-web-services) (AWS) as its cloud infrastructure. Since Anthropic's refusal to support autonomous weapons development and domestic surveillance efforts, other AI firms, including [OpenAI](https://www.wikiprompt.org/wiki/openai), have been brought in to take over that role. These companies provide the underlying [transformer](https://www.wikiprompt.org/wiki/transformer) architectures and [neural networks](https://www.wikiprompt.org/wiki/neural-network) that power military AI systems.

## Involved State Actors

In 2024, the United States Department of Defense had over 800 active AI-related projects and requested $1.8 billion in AI funding, with Project Maven and Project Artemis (AI-resistant drones developed together with Ukraine) being the main ones. The technology has been used in Iran, Iraq, Syria, and Yemen to identify targets. The U.S. military's adoption of AI reflects a broader trend toward [generative AI](https://www.wikiprompt.org/wiki/generative-ai) and [machine learning](https://www.wikiprompt.org/wiki/machine-learning) in defense applications.

China is pursuing "intelligentized warfare," integrating AI across all combat domains - land, sea, air, space, and cyber - with military AI spending exceeding $1.6 billion annually. Other nations, including Russia, the United Kingdom, and Israel, have also invested heavily in military AI capabilities, though detailed public information is limited.

## International Regulation

Since 2014, states meeting within the framework of the Convention on Certain Conventional Weapons have discussed lethal autonomous weapon systems. In 2016, the treaty's states parties established an open-ended Group of Governmental Experts on Lethal Autonomous Weapons Systems to continue those discussions. The discussions have addressed international humanitarian law, accountability, possible prohibitions and regulations, and the extent of human control required over AI-enabled weapons.

Despite these efforts, no binding international treaty has yet been adopted to regulate AI in warfare. Debates continue over the definition of autonomy, the role of human judgment, and the application of existing laws of war to AI-assisted targeting.

## Related Terminology

In 2018, the term "hyperwar" was coined to refer to algorithmic or AI-controlled warfare with little to no human decision-making. This concept highlights the potential for AI to accelerate conflict beyond human comprehension and control. Other related terms include "lethal autonomous weapon systems" (LAWS), "intelligentized warfare," and "AI-assisted targeting."

## Ethical and Operational Concerns

AI warfare raises significant ethical concerns, including the risk of civilian casualties, the potential for algorithmic bias, and the challenge of accountability for decisions made by machines. The Lavender and Gospel systems in Gaza, and the Maven system in Iran, have been criticized for enabling strikes with high civilian death tolls. Proponents argue that AI can improve accuracy and reduce collateral damage by processing more information than humans can.

Operationally, AI systems can be vulnerable to adversarial attacks, data poisoning, and technical failures, as illustrated by the erroneous USSOCOM report in 2026. These risks underscore the need for robust testing, human oversight, and international norms.

## See Also

- [Military applications of artificial intelligence](https://www.wikiprompt.org/wiki/military-applications-of-artificial-intelligence)
- Lethal autonomous weapon
- [Lavender](https://www.wikiprompt.org/wiki/lavender)
- Project Maven

## External links

- [Wikipedia: AI warfare](https://en.wikipedia.org/wiki/AI_warfare)

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Source: https://www.wikiprompt.org/wiki/ai-warfare
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-11-09T12:23:24.118941+00:00