Cognizant Ocean: Data and AI Crucial to Sustainable Shipping

Stig Martin Fiska, Global Head of Cognizant Ocean
Stig Martin Fiska, Global Head of Cognizant Ocean, says shipping should leverage emerging technologies such as AI in a bid to mitigate ongoing challenges

The international transportation of commercial goods and equipment is heavily dependent on shipping, with more than 80% of the journey taking place on water according to UN Trade and Development (UNCTAD).

However, the industry inevitably faces countless disruptions on a daily basis, from extreme weather and industrial action to the kinds of geopolitical incidents seen over the past few years. 

The UNCTAD reports that, by the first half of February 2024, 586 container ships had been rerouted due to ongoing militant attacks on merchant vessels in the Red Sea, while container tonnage crossing the canal fell by 82%. 

Meanwhile, the tragic collapse of the Francis Scott Key Bridge in Baltimore in March saw the major US port close for more than a month, costing the US economy at least US$15m per day.

Stig Martin Fiska, Global Head of Cognizant Ocean, a leader in ‘Blue Economy’ solutions, says shipping should consider leveraging emerging technologies such as AI in a bid to mitigate these challenges.

He explains: “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 – such as navigating the ship or managing activity at a port.

Global shipping is facing a number of challenges

“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 at the same time working to decarbonise our oceans.”

Leveraging AI to navigate unpredictability

Potential disruptions during the shipping journey can, of course, make predictability a challenge to achieve. Enter generative AI (Gen AI), which can be deployed to minimise the need to play a guessing game.  

Each port only has so much capacity, meaning if too many ships arrive at once, waiting times are likely to skyrocket and the extra fuel used by stagnant ships will create a large carbon footprint. 

Here, Gen AI tools can be used to analyse past arrival information to predict when ships should arrive at the port to minimise disruption

Generally speaking, companies possess a lot of data in silos, but lack the knowledge or resources to be able to analyse and make use of it. 

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Stig points to the task of fuel management, which is still often done manually with decisions made based on past experience. 

“An opportunity arises here to combine the power of Gen AI with large language models (LLMs) to document, and therefore automate, these processes, saving shipping crews time,” he adds. 

“With these new, technologically-powered processes in place, shipping companies can make use of the wealth of data they own to make informed decisions.”

Elsewhere, Gen AI can be deployed alongside LLMs to identify factors that impact disruption, such as severe weather and geopolitical issues, and alert staff to take steps to mitigate this.

Pressure on shipping to be more sustainable

As environmental damage to oceans accelerates, so does regulatory pressure on shippers to make their operations more sustainable

In December 2023, the UN General Assembly adopted two resolutions highlighting the rising threats faced by oceans, representing a crucial step towards its goal of conserving at least 30% of marine and coastal areas by 2030.

For the shipping industry, the primary concern in this area is resolving how to prevent ships from causing damage to oceans and their biodiversity. 

Pressure is on the shipping industry to be more sustainable

Once again flying the flag for AI, Stig continues: “Gen 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.”

Gen AI trust issues persist

Ever since ChatGPT was catapulted into the mainstream in late-2022, the buzz surrounding AI has been pretty much inescapable. 

However, given such technologies are still rapidly advancing, it's no surprise to see that many in the shipping industry remain reluctant to put their faith in the suggestion of a Gen AI tool over years of human experience. 

Stig’s answer to this is that these tools should be used as part of a wider holistic decision-making process, with a human still required to validate results. 

“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 analysed at once,” Stig adds. 

“This offers workers in the industry the chance to upskill and use exciting modern technologies within their work, while helping to reduce costly and time-consuming disruptions. 

“Meanwhile, greater efficiency will help organisations meet their environmental goals while attracting customers and investors – all of whom are becoming increasingly sustainably-minded.”

Shipping stakeholders should work as one when it comes to implementing AI

Teamwork crucial to AI implementation

Scepticism isn’t the only problem looming over the implementation of AI.

From the ship itself, to the delivery company, to the port, numerous stakeholders are involved in the shipping ecosystem. 

To make the most of AI technologies, it’s important these stakeholders work together as one to break down information silos and, in turn, improve the quality of operational insights. 

This is particularly crucial given that coordinating all the data involved is complex and many lack the necessary resources, such as personnel or finances, 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,” Stig advises.

“Even a small attempt at becoming more sustainable can reduce carbon emissions greatly. 

“Looking forward, making operations as efficient as possible while working to decarbonise our oceans is paramount as the world becomes more geopolitically, environmentally and financially unpredictable.”

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