Seaports are dabbling in AI, but complex supply chain operations make adoption a challenge

The Port of New Orleans has partnered with the New Orleans Public Belt Railroad and UTC Transoceanic to incorporate artificial intelligence into its cargo logistics. This move, initiated in late May, aims to streamline the transportation of oversized cargo, such as power transformers and industrial generators, using digital twins and real-time data analysis.

The primary advantage of AI implementation is increased speed and accuracy in determining feasible routes, taking into account factors like bridge clearance heights and maximum weights. As of now, AI adoption in US ports is slow due to a cautious approach and cybersecurity concerns. Other seaports, including Corpus Christi and Los Angeles, have also started implementing AI for vessel tracking and optimizing truck appointment systems.

Georgia Ports Authority is exploring AI-based facial recognition for truck drivers. However, the widespread integration of AI at ports remains limited, as these facilities tend to adopt new technologies with a delay of around five years compared to other industries. The integration of AI faces challenges such as cybersecurity risks, the use of outdated systems, and the complexity of coordinating multiple stakeholders involved in the supply chain.

Despite these hurdles, AI holds promise for enhancing efficiency and decision-making in port operations, with potential applications ranging from cargo assessment to administrative tasks.