As the conflict between the United States and Iran intensifies, the US military is increasingly relying on Artificial Intelligence for precision strikes. During Operation Epic Fury, the US military utilised AI to execute precision strikes on Iran.

The US military relies on Project Maven, a major Pentagon initiative designed to integrate artificial intelligence into combat operations. This algorithmic warfare programme processes vast amounts of battlefield data significantly faster than human analysts.

US Central Command actively uses machine learning algorithms to pinpoint hostile targets. Schuyler Moore, CENTCOM's Chief Technology Officer, has previously confirmed that AI systems play a critical role in identifying threat locations across the region.

The system uses advanced computer vision to rapidly analyse satellite imagery and live surveillance drone feeds. It instantly detects minute changes on the ground, successfully identifying hidden missile launchers and newly constructed military facilities.

By automating intense data-processing tasks, artificial intelligence drastically reduces the time it takes to identify and track a target. This shortened 'kill chain' accelerates military decision-making, allowing US forces to strike before the enemy can relocate.

By automating intense data-processing tasks, artificial intelligence drastically reduces the time it takes to identify and track a target. This shortened 'kill chain' accelerates military decision-making, allowing US forces to strike before the enemy can relocate.

Despite these advanced capabilities, the AI does not autonomously engage targets or deploy weapons. Human operators must mandatorily verify every single AI targeting recommendation to ensure strict command accountability and ethical oversight.

The integration of artificial intelligence into major combat operations marks a permanent shift in military strategy. By processing intelligence at unprecedented speeds, the US military maintains a significant tactical advantage over Iranian defence networks.