The Silent AI Revolution in Shipping

Without a doubt, the ongoing technological developments brought on by the emergence of AI changed how we live, work and conduct our daily business. However, the technical applications and advantages of industry-specific AI tools in various business areas has received far less media attention and academic research compared to the vast volume of material publicized on the social, political and macroeconomic effect of generative AI tools, such as ChatGPT. Studies on the application of AI to shipping are particularly rare. Munim et al. found only 56 articles when conducting a keyword search in the literature on the ISI Web of Science database. Therefore, this article will attempt to summarize the various uses of specific AI tools in maritime logistics and explore their potential benefits.

Potential Applications for Operators

AI has numerous applications in the maritime industry. On its most basic level, using algorithms empowered by data collected from onboard surveillance systems and cameras, AI can assist real-time decision making of a ship’s crew via analysing the status of the vessel and its environment (Hemanth). A different application of ship-surveying AI can help to detect anomalies with the ship’s components and, taking into consideration environmental factors like the temperature and weather, identify maintenance problems beforehand when the cost and size of maintenance needed is smaller (Hemanth). With respect to navigation, AI can be as simple as a sensor-based onboard system used to avoid potential collisions to highly complicated predictive and centralized systems used to optimize ship routing to cut costs and fuel consumption. Similar systems used to optimize fuel consumption are also used to reduce carbon emissions as well (Hemanth). In its most advanced level, AI can be used to fully automize a ship’s management and port operations, and be used to operate crewless vessels (Hemanth). However, the industry has not yet developed the technology to safely operate unmanned vessels. Developing automation, however, is sure to revolutionize the industry by greatly increasing efficiency and cutting costs. Victor Szilagyi, Head of Product at Sedna AI claimed in an article published in Hellenic Shipping News that according to DNV, simple automation can reduce operating costs by around 30%. 

The solutions mentioned can lead to positive outcomes such as increased efficiency of ships and allowance for optimizing operations, targeting and reduction of costs via preventive (e.g. preventive maintenance) or active (e.g. collision avoidance systems) measures. However, one should not limit the applications of AI in the industry to the areas in which efficiencies can be gained via optimization, usually enacted and pursued by shipping companies themselves. There is a wide range of tools that focuses on tackling the problems of stakeholders, including clients, regulatory bodies, shareholders and creditors, that can improve transparency and reliability as well as the enforcement of set standards for the industry. These applications will be considered in the next section.

Potential Applications for All Stakeholders

Beyond optimization and onboard processes, AI can be used to deliver solutions to all stakeholders including ship operators themselves. The first of those is container tracking and real-time freight visibility. This helps clients to plan according to accurate time of arrivals and predict delays (Windward), while helping operators to benefit from being transparent to their clients. At the same time, it can also help regulators to keep track of the sources and transfer of goods for customs or sanctions purposes.

Moving on with sanctions enforcement, it is without a doubt that using AI to mark suspicious vessels and screening them against sanction lists as well as conducting due diligence on potential business partners will greatly improve such enforcement (Windward). As mentioned in my last SEG Bocconi article, The Black Fleet: An Introduction to Shipping Sanctioned Oil in 2023, the main ways to avoid sanctions are to conduct unauthorized ship-to-ship transfers and to use shell companies. As such an AI tool used both by regulators and by operators can significantly tighten sanctions enforcement for the benefit of all stakeholders involved by tracking suspicious movements of ships and cargo, as well as using business intelligence data to mark companies that are likely to be fronts for sanctions evasion. 

Furthermore, AI can be used to plan just-in-time delivery schedules that allows all stakeholders to exercise better control over their commercial planning, which not only optimizes cost control and fuel consumption (European Union) but also helps clients to predict their deliveries of goods and make their business plans accordingly. This technology is different from tracking applications, since delivery schedules as opposed to real-time tracking, concerns the planning of the best optimal delivery route that can satisfy the commitments of all stakeholders involved in the process. Meanwhile, container tracking is complementary to these plans since it empowers clients to make active and real time adjustments to the already set business plan formed according to the delivery schedule.

Silence, A Lack of Attention and Strategy on Maritime AI

As the European Union source mentioned in the last section suggests, the EU actively advertises the application of AI to the shipping industry. However, it should be noted that the EU does not have a dedicated strategy for adopting AI in maritime logistics: It only has a maritime security strategy whose objective is to secure the flow of goods in supply chains, of which the maritime shipping industry is clearly a part of. Instead, the adoption of AI is a subtopic of other EU strategies such as the Maritime Security Strategy and the Sustainable Blue Economy Partnership (which itself is a part of the Green Deal). This lack of strategy is not only limited to the EU. Similarly, the United States or the United Kingdom also lack strategies on encouraging and regulating the adaptation of AI. Furthermore, as mentioned in the beginning of this paper, there is a lack of academic research and discussion around the adaptation of AI in the industry, especially those focused not on technical analyses of AI technologies in shipping but the quantitative effects on business outcomes in the industry. This is concerning in the light of the great interest shown by businesses evidenced by a supermajority of maritime logistics companies stating they either actively applied AI solutions in their business or were in the process of testing such solutions via pilot programs (Hellenic Shipping News). 

The most obvious risk is losing ground to China. According to Munim et al. the publishers of largest number of articles regarding the application of AI in the shipping industry is China. Despite the fact that the number of research papers on the topic is still extremely low, most of those papers are produced by elite Chinese universities. In light of the current tensions with the country, becoming dependent on AI products used in a strategic industry would be greatly harmful for the strategic position of the EU. In addition, an inability to comprehend the disruptive effect of AI on the sector, and its overall effects on business outcomes, would be a barrier to a smooth transition of the sector to a new age. Therefore, unless greater attention and resources are devoted to draw attention and publicize the “silent” revolution in the shipping industry and encourage research, it is likely that the maritime industry will suffer in the medium term.


As can be seen from the sources, the shipping industry has a wide range of areas in which AI can be used to improve business functions and promote efficiency and sustainability. However, during the course of my search, I have found a highly concerning lack of academic studies quantifying the effects of AI and linking them to business improvements, a situation also remarked on in my recommended reading and Munim et al. Due to the ever-changing nature of AI and its highly disruptive effect on the conduct of business operations worldwide, I hope that we can see the emergence of this topic as a concern to be researched in the near future by scholars and business intelligence agencies alike.

Recommended Readings

A discussion on how to apply AI in navigation based on international regulations for preventing collusions:

Although not focusing on the effects of AI to the shipping industry and to businesses, this study may be useful for a more technical description on potential uses of AI in shipping:

Cover Image Source


European Comission Directorate General for Maritime Affairs and Fisheries. “AI Boosts Maritime Commerce Thanks to Seaber Software and BlueInvest.” Oceans and Fisheries, 6 Nov. 2023,

hellenicshippingnews… From ChatGPT to Machine-generated Art, AI Is Everywhere. How Can It Optimise the Maritime Industry? | Hellenic Shipping News Worldwide.

Hemanth. “Leading Artificial Intelligence (AI) Companies for the Shipping Industry.” Ship Technology, 21 Dec. 2022,

Munim, Ziaul Haque, et al. “Big Data and Artificial Intelligence in the Maritime Industry: A Bibliometric Review and Future Research Directions.” Maritime Policy & Management, vol. 47, no. 5, July 2020, pp. 577–97.

Windward. “What Is Maritime AITM?” Windward, 24 May 2023,,delays%20and%20offer%20accurate%20ETAs.

Emre Oktav
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