US-Iran war: How AI is reshaping the battlefield
What's the story
The ongoing conflict in Iran has witnessed an unprecedented level of speed and precision, thanks to months of meticulous planning, a massive military buildup, and the use of cutting-edge technology: artificial intelligence (AI). The US and Israeli forces have been using AI tools to gather intelligence, select targets, plan bombing missions, and assess battle damage at an unprecedented pace.
Intelligence gathering
Israel's long-standing reliance on AI for intelligence gathering
Israeli intelligence services have been using hacked Tehran traffic cameras and senior officials' communications to gather information for years. The country has increasingly relied on AI to deal with the massive amount of data from these intercepts. This strategic advantage was evident when Israeli fighter jets fired ballistic missiles at Iran's Supreme Leader Ali Khamenei's residence a week ago, marking the start of the current regional war.
Strategic advantage
AI's role in military logistics and weapon selection
AI is also proving instrumental in managing military logistics, such as ammunition and spare parts supplies. It enables commanders to select the most suitable weapon for each mission. AI-powered machine vision can rapidly identify large numbers of targets, even pinpointing specific aircraft or vehicle models or people. This use of artificial intelligence in military operations is not new for Israel, which has been using it since at least the October 2023 Hamas attacks.
Reconnaissance
AI can help survey success of a strike
Following a strike, AI accelerates battle damage assessment by using image-processing software to streamline initial intelligence. Although analysis depends on image quality and environmental factors, AI is transforming the field through sensor fusion. By synthesizing visuals, radar, thermal signatures, and mass spectroscopy, AI generates rapid conclusions. This fast evaluation of attack success helps commanders refine subsequent targeting lists, creating a more efficient intelligence cycle that overcomes the limitations of traditional manual review.