The U.S. Navy is expanding its use of artificial intelligence to improve detection and countermeasures against Iranian naval mines in the Strait of Hormuz, a critical maritime chokepoint for global energy and commercial shipping. A recently awarded contract highlights efforts to accelerate underwater mine detection using machine learning systems designed to support unmanned operations in contested waters where traditional mine-clearing methods remain slow and hazardous.
According to the contract, the Navy has allocated up to $100 million to San Francisco-based Domino Data Lab to strengthen its AI-driven capabilities for maritime operations. The system is intended to enhance how underwater drones identify and classify naval mines, including previously unseen types, by rapidly training and updating detection models used in operational environments.
The Strait of Hormuz has remained a central focus of maritime security concerns amid heightened tensions involving Iran. President Donald Trump has stated that the U.S. Navy is actively engaged in clearing Iranian mines from the waterway, which serves as one of the world’s most important routes for oil shipments. Any disruption in the strait is considered a significant risk to global energy markets, with mine-clearing operations expected to take extended periods even under current ceasefire conditions between the United States and Iran.
The AI effort falls under the Navy’s broader Project AMMO, or Accelerated Machine Learning for Maritime Operations, which is designed to speed up and improve underwater mine detection. The software integrates multiple sensor inputs, including side-scan sonar and visual imaging systems, and enables real-time monitoring of AI model performance. It also allows operators to identify detection failures and deploy updates more quickly than traditional systems permit.
A central objective of the program is reducing the time required to adapt detection systems to new threats. Previously, updating machine learning models for unmanned underwater vehicles to recognize new or unfamiliar mines could take up to six months. With Domino’s platform, that timeline has reportedly been reduced to days, significantly improving operational responsiveness in dynamic conflict environments.
Thomas Robinson, Domino’s chief operating officer, described the shift in mine warfare technology, stating, “Mine-hunting used to be a job for ships. It’s becoming a job for AI. The Navy is paying for the platform that lets it train, govern, and field that AI at a speed required for contested waters that block global trade and imperil sailors.”
The urgency surrounding mine detection efforts is shaped by the scale and sophistication of Iran’s naval mining capabilities. According to estimates cited by U.S. defense intelligence, Iran possesses more than 5,000 naval mines and has begun deploying them in strategic waterways. The geography of the Strait of Hormuz further amplifies the threat, with narrow shipping lanes and shallow waters creating conditions that favor rapid mine deployment and complicate clearance efforts.
Iran’s arsenal includes multiple types of naval mines developed over decades, including moored mines that float beneath the surface, bottom mines that rest on the seafloor and use sensors to detect passing vessels, and limpet mines that can be attached directly to ships by divers. These systems are designed not only to sink vessels but also to disable them, often rendering ships inoperable through what militaries describe as “mission-kills” rather than complete destruction.
Clearing such mines remains a complex and time-consuming military task. Detection often relies on sonar-equipped unmanned systems conducting systematic sweeps of underwater terrain, while neutralization can require either remote detonation or direct intervention. Historical operations have demonstrated that even under ideal conditions, mine clearance can take weeks or months, particularly when conducted in active or contested environments.
Recent military activity has also targeted Iran’s mine-laying capability directly. U.S. Central Command has reported strikes on multiple Iranian vessels believed to be involved in deploying mines, reflecting a broader effort to reduce the threat before it reaches critical shipping lanes. Despite these measures, officials have indicated that mine warfare remains a persistent challenge, with relatively low-cost deployments capable of forcing extensive and costly counter-operations.
As tensions in the region continue to shape maritime security planning, the integration of AI systems like those developed by Domino represents a shift toward faster, software-driven responses to underwater threats. The Navy’s investment underscores an increasing reliance on automated detection systems to manage risks in strategically vital waterways where traditional mine warfare continues to pose a significant operational and economic challenge.