Looking forward, making operations as efficient as possible while working to decarbonize our oceans is paramount as the world becomes more geopolitically, environmentally and financially unpredictable.
The international transportation of commercial goods and equipment is heavily dependent on shipping; over 80% of the journey is through water. However, the shipping industry faces countless disruptions every day, whether it’s severe weather, geopolitical troubles or industrial strikes. Recently, disruptions in the Red Sea meant that by the first half of February 2024, 586 container vessels had been rerouted, while container tonnage crossing the canal fell by 82%. Last year, drought in Panama caused reduced traffic through the canal by a third and increased shipping costs. In March 2024, the Baltimore bridge collapse catastrophe caused one of America’s largest ports to close, costing the U.S. economy an estimated $15 million a day.
To mitigate these challenges, the shipping industry should look towards leveraging innovative technologies such as artificial intelligence (AI). AI has the potential to reimagine the way the shipping industry can predict and circumvent disruption, ensuring different parts of the supply chain run seamlessly, whether navigating the ship or managing activity at a port.
At the same time, as climate change soars, the shipping industry, akin to most sectors, is experiencing increasing pressure to become more sustainable. To ensure long-term success, efforts to become more sustainable need to go hand-in-hand with encouraging business growth. By implementing innovative technologies, shipping companies can improve their bottom line through increased efficiencies, while simultaneously working to decarbonize our oceans.
Potential disruptions in the shipping journey can make predictability a challenge to achieve. However, generative AI technologies can be deployed to minimise the need to play the guessing game. For example, a singular port only has so much capacity, and if too many ships arrive at once, waiting times may skyrocket, while the extra fuel used by stagnant ships creates a large carbon footprint. Here, generative AI tools can be used to analyze past arrival information to predict when ships should arrive at the port to minimize disruption.
Often, companies own a lot of data in silos but lack the knowledge or resources to be able to analyze and make use of this data. For example, take the task of fuel management. This is still often done manually by employees, with decisions made based on past human experience. The opportunity arises to combine the power of generative AI with large language models (LLMs) to document and therefore automate these processes, saving shipping crews time. With these new technologically powered processes in place, shipping companies can make use of the wealth of data they own to make informed decisions.
As another example, generative AI can be deployed with LLMs to identify factors that impact disruption, such as severe weather and geopolitical ongoings, and alert staff to take steps to identify factors that impact disruption, such as severe weather and geopolitical ongoings and alert staff to take steps to mitigate this.
As environmental damage to our oceans accelerates, subsequently so is regulatory pressure on the shipping industry to mitigate sustained damage. In fact, in December 2023, the United Nations General Assembly adopted two resolutions that highlighted the rising threats our oceans are facing, a crucial step towards its goal to conserve at least 30% of marine and coastal areas by 2030. The White House Ocean Climate Action Plan (OCAP) targets incentives and regulations for decarbonization, new green shipping corridors and in general a clear direction toward a cleaner future for marine transportation. Couple that with The National Ocean Biodiversity Strategy (NOBS) that aims to minimize disruptions to marine ecosystems, not unlike the UN’s goal of conserve 30% of marine and coastal areas by 2030, mean massive changes and incentives to how marine shipping will be able to operate in the near future.
For the shipping industry, the priority concern is how ships can avoid causing damage to the oceans and its biodiversity. Generative AI and LLM tools can be used to create an effective environmental impact monitoring system. For example, port congestion is a large contributor to local air pollution, but a tech-enabled system can forecast and therefore reduce congestion to decrease air pollution. Meanwhile, the risk of bringing invasive species to local ecosystems is a concern, but an AI-powered system can track vessels to provide advanced warning of invasive species risks.
Despite the buzz around AI technologies, these tools are still rapidly advancing, so it’s no surprise many in the shipping industry are reluctant to put their utmost trust in what a generative AI tool suggests over their own years of human experience. However, these technologies would be used as part of a holistic decision-making process; a human will always need to validate the results, but these technologies can offer more reassurance that the most appropriate action is being taken on the shipping journey based on thousands of pieces of real-time data, all analyzed at once.
This can offer workers in the industry the chance to upskill and use exciting modern technologies within their work, while helping reduce costly and time-consuming disruptions. Meanwhile, greater efficiency will help organizations meet their environmental goals while attracting customers and investors – all of whom are becoming increasingly sustainably minded.
However, human skepticism isn’t the only problem looming over the implementation of AI tools. From the ship itself to the delivery company to the port, there are many stakeholders involved in the shipping ecosystem. To make the most of AI technologies, the shipping industry must work together to break down information silos and in turn improve the quality of operational insights. However, coordinating all the data involved is difficult, especially when many often lack the resources – whether personnel-wise or financially – to focus on innovating digitally.
Rather than seeing implementing AI as a huge project that needs everyone’s buy in, shipping companies should take it step by step. Even a small attempt at becoming more sustainable can reduce carbon emissions greatly. Looking forward, making operations as efficient as possible while working to decarbonize our oceans is paramount as the world becomes more geopolitically, environmentally and financially unpredictable.
