Digitalisation in Shipping

 

Digital Disruption and the Future of Maritime Transport

Maritime transport is on the brink of a profound technological shift—likely the most significant in its history—driven by digitalisation, often referred to as the third major maritime technological revolution. This transformation involves the adoption of advanced digital tools and data analytics, including machine learning, which support and automate decision-making processes.

The scale of this digital disruption is such that, in the near future, nearly every aspect of maritime operations will be reshaped. Some existing businesses will contract or disappear altogether, while others will evolve or merge. Simultaneously, new sectors and services will emerge, fundamentally changing how maritime business is conducted. The timing of this disruption is linked to breakthroughs in three core areas of digital technology, enabling enhanced automation and the ability to uncover previously unknown patterns in maritime activities.

While the long-term trajectory of this digital revolution is relatively clear, specific details—such as when and where changes will occur, and who will lead them—remain uncertain. This is due both to the early stage of the transformation and the rapid pace of technological advancement, as well as the varying capabilities and resistance among industry participants. The following sections will explore the key drivers and underlying causes of this shift and offer insights into the potential features of a digitally transformed maritime sector.

 

Examining Shipping and Related Functions

At its essence, maritime transport involves moving goods across locations by ship—the sector’s primary function and end product. However, numerous interconnected tasks are required to make this possible. To fully understand how digitalisation will impact the shipping industry, it is necessary to examine the digital characteristics of both core and supporting activities. Key questions include: What constitutes the central function of shipping? What inputs are necessary? How are costs incurred and revenues earned? This analysis will approach the structure of shipping-related operations from three angles: the core shipping function, the relationship between outputs and inputs, and the overall cash flow framework.

 

What are the shipping-centric maritime activities?

At the heart of maritime transport lies the movement of cargo by ship from one port to another. All other maritime services exist to support this core activity. Since shipping companies are responsible for carrying out this central function, it’s important to understand the broader system that surrounds and enables it.

Over the centuries, maritime transport has developed into a vast and intricate network centered around cargo shipping, supported by numerous auxiliary services. Shipping costs are typically divided into three categories: capital costs, operational costs, and voyage costs. In the same way, supporting maritime activities can be grouped into ship-related, operation-related, and voyage-related services, as outlined below:

● Ship-related activities: These include ship construction, maritime financing from banks or financial institutions, ship classification (spanning from design to decommissioning), and marine insurance services.

● Operation-related activities: This group encompasses ship operation and management, technical management, crew management, seafarer education and training, ship maintenance and repairs, and regulatory functions such as ship registration. Often, shipowners outsource technical and crewing responsibilities to specialized third-party firms.

● Voyage-related activities: Focused on cargo transportation, this includes maritime legal services related to chartering agreements, freight payment disputes, and cargo insurance claims.

Additional services provided at ports include bunkering and ship supply, tailored to the ship type and trade it is engaged in. Commercial services such as shipbroking and port agency are also part of this framework, alongside cargo and port handling operations that serve both vessels and their cargoes.

Today’s maritime industry functions as a complex system built around ship operation and management, supported by roughly 11 main activity areas. While the structure presented is representative rather than exhaustive, it reflects a shift from the past, when a single shipowner or trader handled all responsibilities. Over time, increased specialization has led to the separation of these functions into distinct industry sectors.

 

How can maritime activities be characterised by their outcomes and inputs?

Maritime activities can also be examined through the dual lenses of outcomes and inputs. This approach focuses on 11 core functions of the maritime industry and considers, on one hand, the intended outcome or purpose of each activity, and on the other, the key inputs required to perform it. Since all these tasks are carried out by people, this method also reflects a human-centric view of maritime operations.

The core of maritime operations lies in ship operation and management, both onboard and ashore. The desired outcome is the successful transportation of goods between ports. This physical movement of cargo relies on seafarers making informed decisions based on ship conditions, navigational data, and voyage instructions. Their judgment and expertise, shaped by training and experience, are crucial for interpreting this information and ensuring the transport proceeds efficiently. Here, the outcome (cargo movement) is dependent on effective input (information, skills, and decision-making).

This same framework can be applied to the other ten principal maritime activities. Though today they operate independently, historically they were performed together by a single shipowner or trader before the industry evolved and became specialised. As maritime trade expanded, separating these functions increased productivity and efficiency. Below is a summary of these activities based on their outcomes and inputs:

• Shore-based ship operation and management: Carried out by shipping companies, this activity results in commercial decisions and guidance for crews and ships. Inputs include operational data and market intelligence.
• Shipbuilding and repair: Considered part of the broader maritime industry, this activity delivers the physical ships used in transport. Inputs involve construction materials, labour, and technical specifications.
• Ship financial services: Financial institutions provide funding for ship acquisition. The outcome is financing arrangements. Required inputs include client evaluations and market risk assessments.
• Classification of ships: Classification societies develop and verify technical ship standards. The result is certification of compliance. Inputs include regulatory frameworks and engineering data.
• Marine insurance: This provides financial coverage for risks during transport. The outcome is loss compensation or claims settlement. Inputs include incident reports, policy terms, and assessments.
• Shipbroking and agency: These intermediaries facilitate the negotiation and conclusion of shipping contracts. The outcome is the signing of agreements. Inputs include business knowledge and client information.
• Port and cargo handling services: Port operators ensure berthing and efficient cargo loading/unloading. The outcome is smooth port operations. Inputs include infrastructure, handling equipment, and communication from ships and shippers.
• Maritime legal services: Lawyers and legal firms handle contracts, disputes, and claims. The outcome is legal resolution or documentation. Inputs include legal expertise and case-specific information.
• Ship registration: Public authorities manage vessel registration and related oversight. Outcomes include official registration and regulatory control. Inputs include policy directives and vessel information.
• Maritime education and crew management: Maritime academies and management firms train seafarers and manage crewing. The outcome is a competent maritime workforce. Inputs include curricula, training programs, and labour data.

In summary, while the outcomes of maritime activities differ—ranging from physical goods movement and shipbuilding to legal documentation and insurance—their inputs are more uniform. Most rely on data, expertise, and instructions, highlighting the central role of information processing and human judgment in the maritime industry.

 

 

How does a cash-flow perspective shape our understanding of maritime activities?

The core function of transporting cargo by sea stands out among maritime activities due to its unique role as the primary generator of external cash flow. As the final service delivered to global trade, cargo transport by ship is the only maritime activity directly funded by outside sources, specifically through freight payments from international trade. All other maritime services are internally financed, with shipping companies allocating portions of their freight income to pay for supporting services. This inward cash flow from freight is then distributed outward across the sector, reinforcing the central role of ship operation while positioning other services as auxiliary.

Although the precise flow of money through each maritime activity is hard to quantify, there are clear distinctions in scale. Some activities command large cash shares due to the value they provide, while others are smaller or closely tied to core operations. Based on the structure of these flows, maritime activities can be grouped into four categories: ship operation, ship acquisition, port operations, and maritime services. Much of the revenue received from freight is redirected from shipping companies to these areas:

● Ship Operation: At the heart of the industry, ship operation is the only segment compensated directly by customers outside the maritime system—shippers. The overall size of the maritime freight market is difficult to pin down due to its volatility, but it’s generally estimated to account for around 5% of the total global import value. From this income, shipping companies fund essential goods and services to maintain operations.

● Ship Acquisition and Financing: The purchase of ships represents the first major investment for any shipping company. These assets are costly, often worth tens to hundreds of millions of dollars each. Capital expenses—including the purchase of ships, containers, and maintenance—are estimated to represent 10% to 15% of the total freight revenue.

● Port Operations and Cargo Handling: Port-related expenses can be divided into service-based costs (e.g., dues, handling, storage) and time-based costs (e.g., ship and cargo idle time in port). On some routes, ships may spend more time docked than sailing, and the value of idle time can be extremely high. As a result, shipping companies dedicate a large share of freight earnings to cover port services and infrastructure use.

● Maritime Services: This category encompasses a wide array of professional support services, such as registration, classification, financing, insurance, broking, and legal assistance. Labor costs, including seafarers and shore-based personnel, are among the largest expenditures. Fuel and insurance also represent significant and fluctuating expenses that depend on market conditions.

Through this lens, we gain a clearer understanding of the economic dynamics within maritime transport. Examining activities by their interdependencies, inputs and outputs, and financial flows allows us to assess the impact of digitalisation and automation more effectively. These trends are reshaping the skill sets required and influencing the future structure of maritime services. While many support activities will evolve or diminish with technological advancement, the fundamental role of shipping cargo across oceans will persist.

 

Digitisation and Programmability in Maritime Operations

Scientists suggest that at the most fundamental level, matter consists of information—data represented as binary digits, either zero or one. In this sense, everything can be viewed as digital or converted into digital form. While this concept is still debated, in maritime transport, it is reasonable to argue that most activities revolve around managing information and data, which are increasingly capable of being captured, communicated, and processed digitally. If maritime processes are information-driven, then they can, in theory, be conducted digitally.

All the activities discussed in earlier sections are carried out by individuals or teams. In this section, the focus turns to maritime professions and their procedures and methods. Digitisation refers to converting analogue processes or information into digital formats, whereas digitalisation denotes a broader transformation—restructuring systems and operations using digital technologies. Programmability, meanwhile, refers to the extent to which an activity can be standardised and encoded into an automated process.

To better understand this transformation, we will analyse the digitisation and programmability of key maritime activities in three main areas. First, we will examine ship operation and management—both onboard and shore-based—because it is the core activity of maritime transport and serves as the main channel through which cash flows to other maritime sectors. Next, we will explore port operations to identify which aspects are conducive to digital automation and which remain less adaptable. Finally, we will review essential maritime services, evaluating how digitally adaptable and programmable each function is within the evolving maritime landscape.

 

 

To what extent are ship operations digitised and programmable?

Ship operations are jointly managed by shore-based personnel and onboard crew, encompassing three primary domains: financial, commercial, and technical management. Financial management involves decisions on ship purchases and sales, financing, debt servicing, and investment analysis. Commercial management focuses on chartering, route planning, contract negotiations, and coordination with agents and insurers. Technical management includes crew administration, ship upkeep, and repair operations. While these domains differ, they require similar skill sets and are categorized under Maritime Jobs – Category 3: Maritime Managers and Specialists, with core functions such as planning, routing, dispatching, and shipment tracking. The level of digitisation and programmability varies across these areas:

● Financial management: Inputs such as technical specifications and financial data are mostly digital, but elements like economic outlooks, policy shifts, and market competition are more complex and less easily digitised. Standard parameters such as KPIs, credit scores, and loan terms can be programmed due to their rule-based nature. However, since financial decisions often involve negotiations and relationship dynamics, full programmability is still limited.

● Commercial ship management: This includes transport contract negotiations, marketing, and customer service. In sectors like liner shipping, many processes are already digitised, with digital formats used for both inputs and outcomes. While forecasting and strategic decisions remain complex, structured workflows and predefined variables in many cases allow for partial programmability.

● Technical ship management: This covers crew operations and vessel maintenance. Routine tasks, like scheduling and recording maintenance, are suitable for digitisation. However, major repairs still require nuanced human evaluation. Although some parts can be programmed, managing personnel and responding to varied technical conditions reduce the overall programmability.

As for onboard operations, classified under Maritime Jobs – Category 1, they involve navigation and engine-related activities and are largely experience-driven, yet progressively digitised:

● Navigation tasks: Duties such as watchkeeping rely on integrating data, environmental observations, and navigational rules. Systems like ECDIS have replaced paper charts, though some analogue elements still exist and can be digitised. While navigation tasks are theoretically programmable, full implementation requires comprehensive digitisation first.

● Engine operations: These are among the most digitised and programmable areas, especially on ships equipped with unmanned engine rooms. Such systems operate through digital controls and rely on established cause-effect relationships, making engine management highly programmable with minimal human input.

 

 

How digitised and programmable are port operations?

Port operations can broadly be classified into two categories: ship-related and cargo-related. Ship-related tasks encompass safe navigation, bunkering, provisioning, as well as repair and maintenance services. Functions such as maintaining navigational channels and providing navigational aids are largely capable of being digitised. However, services like pilotage and towage present greater challenges for digitisation. The degree of programmability varies—automated navigation assistance in port areas is increasingly feasible, and the delivery of bunkers, water, and supplies can be partly digitised and automated, provided that supporting systems are properly integrated. In contrast, ship repair and maintenance activities are often case-specific and complex; while data and routine maintenance processes can be digitised, full programmability is generally limited.

Cargo-related port activities consist of four core operations: ship–shore transfer, cargo movement within the port, storage, and gate operations. These processes are tightly interconnected and must be synchronised to improve overall efficiency—enhancing one aspect in isolation is typically insufficient.

• Ship–shore handling involves loading and unloading cargo and is highly standardised and repetitive. It is already widely digitised and increasingly automated in modern ports.
• Cargo transfer refers to moving goods between waterfronts and storage areas using handling equipment. The processes are structured, data-driven, and suitable for automation.
• Storage operations involve holding cargo in yards or warehouses. The information involved is digital, and workflows are programmable.
• Gate operations, which manage cargo delivery and reception, are increasingly handled through digital systems, making them programmable as well.

Most port-related tasks, particularly those performed by stevedores, are repetitive and operational in nature, requiring minimal training. These characteristics make many aspects of port operations well-suited for digitisation and automation, though the level of programmability may vary depending on the complexity of the task.

 

How digitised and programmable are maritime services?

Maritime services, which function primarily in support of shipping companies, exhibit varying degrees of digitisation and programmability. Some services, such as ship finance and marine insurance, contribute significant value, while others like ship registration and legal services play more administrative roles. Due to their supportive nature and shared reliance on communication and coordination, these services are discussed collectively. They typically fall under maritime job categories 2 and 3. Below is an overview of the digitisation of data and the extent to which these services can be standardised and programmed.

● Ship registration: Information related to the ship, its owner, and registration conditions can be fully digitised. The process generally follows a standard format, although exceptional cases may require individual attention. Most of the workflow is programmable.

● Marine insurance: As a specialised area, marine insurance requires considerable expertise. While most underwriting data can be digitised, claims handling varies significantly from case to case and often demands tailored investigation, limiting programmability.

● Ship classification: Inputs and outputs regarding a ship’s technical condition can largely be presented digitally. However, physical inspections are still essential, making parts of the process resistant to full automation.

● Shipbroking: The information used in broking is generally digitised, but the nature of the work—which involves contract negotiation, client interaction, and interpretation—makes it difficult to program as it relies on personal judgment and adaptability.

● Ship agency: Agents collect and distribute ship- and cargo-related information, much of which can be digitised. Several logistical and documentation tasks are suitable for programming, making this a partially programmable service.

● Ship finance: Financial institutions require data that can be digitised to evaluate credit and investment. While some financial decisions can follow standard models, forecasting and market analysis still require nuanced human input, though AI is beginning to assist in this area.

● Maritime legal services: Legal professionals work with statutes, contracts, and case files, most of which are in digital format. A substantial portion of their tasks can be standardised, though direct legal representation and strategic counsel remain human-driven.

In conclusion, while many maritime services have embraced digitisation, their programmability depends on the complexity of tasks and the degree of human judgment involved. Although increasing automation is likely, certain areas will continue to require personal expertise.

 

 

Which maritime activities are most compatible with digitisation and programmability?

Digitisation serves as the foundation for digitalisation—it involves converting all relevant maritime information, data, communications, and operational processes into digital formats. Once this foundation is in place, digital technologies and analytical tools can be used to automate decision-making processes, a phase referred to as digitalisation. However, not all maritime decisions or operations can be automated. Only those processes that are less reliant on subjective judgment and can follow structured rules are considered programmable. In the previous analysis, we assessed the digitisation and programmability levels of several key maritime activities. While these levels may vary across regions and over time, the goal was to offer a general perspective on how different activities might be transformed through digital technology.

This assessment can be visualised using a matrix where the horizontal axis represents the degree of digitisation and the vertical axis represents the degree of programmability. Activities such as cargo handling fall into the high-digitisation, high-programmability quadrant due to their repetitive and standardised nature. Shipboard operations also rank high in both categories, along with areas like ship registry, ship agency, and parts of maritime legal services.

Conversely, activities such as shipbroking or ship-related port services tend to be highly digitised but less programmable, as they require case-specific analysis and subjective decisions. Activities like ship finance, marine insurance, and shore-based ship operations are typically placed in the low-digitisation, low-programmability quadrant due to their reliance on personal interaction and complex case management. No activities were identified as having low digitisation but high programmability. Importantly, there is a strong positive correlation between digitisation and programmability (r² = 0.78), indicating that higher levels of digitisation are generally associated with greater potential for automation.

 

 

Technological Breakthroughs and Their Impact on Maritime Digitalisation

Digitalisation represents a shift in how business is conducted, whereas digitisation refers merely to converting information into digital format. A relevant question is why, despite the digitisation of much maritime data, digitalisation itself has lagged behind. To understand this, we must examine why digital transformation in maritime transport didn’t occur earlier and why it is now gaining momentum. The primary reason is that key technological advances essential for digitalisation have only recently emerged. These developments fall into three main categories:

1. Data acquisition
2. Data processing
3. Data mining

Specifically, the first area concerns the ability to gather, transmit, and store data; the second focuses on analytical tools and algorithms that generate insights and value; and the third deals with the enhanced computing power necessary for in-depth data analysis. Each of these areas is discussed in turn below.

Why Is Data Acquisition So Important?

Sound decisions depend on access to accurate and sufficient information. In maritime operations, decisions are frequently made with incomplete data, which can lead to errors or accidents—often due to the absence of crucial information. In this context, data also includes experience and domain-specific knowledge. Thus, the collection, transfer, and storage of relevant and comprehensive data form the foundation of effective digital systems. Let’s examine the progress made in each of these components.

● Advances in Data Collection: Maritime operations already rely heavily on digital communication. Internally, ERP systems have replaced paper records with integrated digital data. Externally, communications with clients and digital documentation—often linked to CRM platforms—are now common. Still, large volumes of uncollected data remain, such as detailed records on crew performance, equipment status, environmental conditions, and market dynamics. This is largely due to technological limitations in gathering and utilising such data. Recent progress in voice and image recognition and the development of advanced, cost-effective onboard sensors are overcoming these challenges. As a result, the maritime Internet of Things (IoT) is expanding rapidly, driving a sharp increase in available data.

● Advances in Data Transmission: Much of the data generated in maritime activities is real-time and must be transmitted immediately for cloud- or edge-based processing. This requires seamless data flow across devices and platforms. Technologies such as fibre optics and wireless communication now enable the efficient transfer of large data volumes. Ship-to-shore communication relies on satellites, while 5G technology is transforming land-based maritime functions. For example, 5G enables high-speed automation in container terminals, facilitating fast, safe, and efficient cargo handling.

● Advances in Data Storage: Handling vast and growing volumes of data presents ongoing storage challenges. Improvements in memory technology, along with the rise of cloud computing and decentralised edge storage, now make it possible to store and process data both centrally and locally. As these technologies evolve, storage becomes more efficient and cost-effective. However, proper filtering, classification, and labelling of data are essential before storage. Not all information—for example, from charter party negotiations—needs to be saved, and sensitive or irrelevant data should be excluded. Accurate labelling is also crucial; for instance, distinguishing between real-time operational data and final outcome data ensures better retrieval and analysis.

 

Why are algorithms vital for extracting value from data?

The true value of big data lies not in its sheer volume but in the ability to uncover insights—patterns, models, and answers—through data analysis. Data serves as a foundational resource rather than a final product; it only becomes meaningful when processed using appropriate analytical methods that lead to informed decisions, solutions, and actions.

In the highly competitive maritime transport sector, the quality of decision-making is critical. This quality depends on both access to sufficient data and the capability to interpret it effectively by identifying relationships among key elements. Poor decisions typically stem from missing or misunderstood data—often labeled as uncertainty or risk.

For instance, a shipowner might invest in a ship with limited demand due to lack of market insight, or a marine insurer might underprice coverage by failing to recognize hidden risks. While digitisation has improved access to data, the core challenge now lies in deriving useful conclusions through algorithms. Two main approaches are used for data processing:

● Expert system method, which simulates the reasoning of professionals by using past data to model best practices. This approach applies algorithms to establish links between input variables and recommended actions. Once a sufficient database of past cases exists, algorithms can be used to evaluate new scenarios similarly to how an expert would. For example, a ship investment analysis can be automated based on known factors and cause–effect relationships. However, such systems are generally limited to familiar situations and struggle with novel or unforeseen circumstances. Their goal is to emulate expert judgment, not exceed it.

● Deep learning, a form of artificial intelligence. Using machine learning algorithms, this approach identifies optimal solutions by working from core principles and desired outcomes, rather than relying on past data. It generates its own logic, independent of previous experience, and is supported by developments in neuroscience. This makes it especially powerful, as it can uncover new, previously unknown strategies. Although deep learning is still in its early stages of application in shipping, it holds significant potential. AI could eventually transform key functions such as route planning, ship scheduling, and collision prevention. Given its capacity to process vast amounts of data far beyond human capability, AI is likely to reveal solutions that surpass what are currently considered best practices in maritime operations.

 

 

Why is computing power a crucial enabler of digitalisation?

The ability to process massive amounts of data in real time relies heavily on powerful computing capabilities. Since the 1960s, computing hardware has seen rapid and consistent improvements, aligned with Moore’s Law, which predicts a doubling of transistors on a chip approximately every two years.

By 2018, top-tier computer chips could perform 10 trillion operations per second, and today’s smartphones already exceed the computational capacity of the room-sized supercomputers of earlier decades. Technological advances such as the development of GPU-based parallel processing have been instrumental in this growth, enabling the rise of artificial intelligence and broader digital transformation.

As digitalisation expands across industries, including maritime transport, the volume of data generated is set to rise exponentially. For example, autonomous ships are expected to produce several thousand gigabytes of data per day, while widespread use of sensors on ships, cargo, containers, and onboard equipment—as part of maritime IoT systems—will demand exceptional real-time data processing power. F

ortunately, computing technology continues to evolve. Researchers are enhancing current systems while exploring transformative innovations like quantum computing and 3D chip structures. A major breakthrough came in 2019 when Google demonstrated that a quantum computer could outperform traditional computers by more than a thousandfold.

Digitalisation, automation, and maritime transport

Digitalisation is often associated with the disruption of established business models, driven by emerging technologies. While such breakthroughs create the foundation for transformation, the true disruption occurs when these technologies generate substantial value for customers.

In maritime transport, this added value primarily emerges in two areas: automating operations for improved efficiency and reliability, and enabling smarter decision-making through advanced analytics. This section focuses on the role of automation. Adopting new technologies often entails significant cost and risk, so companies are unlikely to shift from traditional practices unless competitive forces leave them little choice. However, those that embrace digital tools early—when the operational benefits are clear—can gain a significant advantage.

The ability to create tangible customer value through automation is a critical driver of change. Because digital technologies are advancing so quickly and their maritime applications are still evolving, it’s more useful to identify general trends in digitalisation and automation than to predict exact outcomes or timelines for disruption.

 

What new value does digital disruption bring to shipping?

Contrary to the common belief that digitalisation and automation in maritime transport are primarily about reducing labour costs by replacing humans with machines, the real benefit lies in the additional value these technologies create. Transport customers consistently seek optimal value for money, where quality and cost are closely interlinked. Digitalisation enhances both. To explore this, we examine how digitalisation and automation improve customer value across three core areas of maritime activity: ship operations, port operations, and maritime services. We also compare the conventional approaches with the evolving, tech-driven models.

Onshore Ship Management
The level of digital adoption in onshore ship management remains relatively low. Most shipping companies still operate with traditional structures, where financial, commercial, and technical managers handle largely repetitive and routine tasks. As these processes become increasingly digitised, data mining and algorithms can identify more efficient business models and enhance decision-making. Similar transformations have already occurred in sectors like consulting and legal services. The integration of AI in shore-based ship management is inevitable and will also play a significant role in improving risk management—an area we address in the next section.

Shipboard Management
The concept of autonomous ships has gained traction in the maritime press. Since shipboard operations are largely procedural and routine, automating crew functions is technically achievable and will likely become widespread. For full automation to materialise, the digitisation of all shipboard activities must be advanced. Some experts believe that electrification of ship propulsion is a prerequisite for autonomous vessels, which would depend on future breakthroughs in battery technology. Other modes of transport—such as driverless trucks and high-speed trains in countries like France, Japan, and China—demonstrate how, once automation begins, progress accelerates rapidly through data collection and iteration. For shipping, automation promises to improve safety and service quality by drastically minimising human error.

Port Operations
Automated container terminals are already in operation, where human roles are mainly supervisory. These terminals outperform traditional ones in areas such as crane productivity, cost per TEU, and energy efficiency. Container ports are particularly suitable for automation due to their structured, repetitive workflows in confined, predictable environments. For ship-related port activities, using IoT and AI to analyse real-time data on ships, cargo, weather, and berth availability can dramatically enhance efficiency. Some advanced ports are preparing to introduce remote-controlled pilotage systems and unmanned tugboats. The shift is clear—from labour-intensive, inner-city ports to highly automated, efficient facilities located outside urban centres.

Maritime Services
Maritime services vary widely in how they are impacted by digitalisation. Administrative functions like ship registration follow standard procedures and are highly automatable, improving accuracy and reducing processing time. Information-driven services are especially at risk of being replaced by digital platforms. Contract negotiation roles, such as shipbrokers and chartering agents, could benefit from AI and machine learning, which can improve both the quality and speed of decisions. Even in more traditional services like ship finance, insurance, and legal advisory, where human interaction remains important, AI can provide added value by leveraging broader datasets to produce faster, more accurate insights. Over time, AI may even outperform human professionals by detecting patterns and solutions previously unseen. Maritime education and training will likely be among the last areas to be fully automated, but digital tools are already adding value through personalised e-learning options that support continuous upskilling in a rapidly evolving industry.

 

 

What are the challenges of maritime automation?

While automation and enhanced decision-making are both outcomes of digitalisation, they represent different facets of transformation—each offering significant customer value but also introducing a range of challenges and long-term consequences. These challenges can be examined through various lenses, including economic, social, operational, technical, legal, and regulatory perspectives.

Economic considerations
Assessing the full economic impact of automation in maritime transport is difficult due to many of the associated costs and benefits being indirect or long-term. However, experiences from other industries—such as automobile manufacturing, where robotic automation has become the norm—demonstrate strong economic benefits. The maritime sector has largely embraced the potential of automation, with nearly all major shipping firms and numerous external entities initiating autonomous ship projects by 2019. Several trial runs have been completed, and the Yara Birkeland, a 120-teu electric, autonomous vessel operating along the Norwegian coast, became one of the first commercial examples. In 2018, the first autonomous shipping company, Masterly, was founded. Similar efforts have emerged globally. Research supports the idea that autonomous ship ownership and operation can yield substantial cost reductions. Although construction costs for autonomous ships are higher, savings arise from eliminating crew expenses and reducing fuel use due to the removal of crew accommodation structures, which lowers both weight and drag. These savings become increasingly important amid rising competition within maritime transport and against other modes like road transport. For example, full truck automation could erode short-sea shipping’s cost advantage. In Qingdao, China, the cost to develop a fully automated container terminal was around 150% higher than a traditional one, yet within its first year of operation, the terminal achieved notable efficiency gains. Labour was cut by 85%, and average crane productivity reached 35 moves per hour—a 30% improvement over manually operated systems. With annual operator wages at around $18,000, payback for the additional investment is estimated at 5–7 years. Though the full economic impact of autonomous maritime operations is still unfolding, the benefits clearly extend beyond just cost savings.

Social implications
The social impact of maritime automation is among the most pressing concerns, as the shift affects not only seafarers and port workers but nearly all jobs within the sector. No position is entirely immune to automation. Rather than forecasting job losses or timelines, it is more meaningful to evaluate the likelihood of job automation based on the specific skills, knowledge, and responsibilities each role entails, and how these match with existing technological capabilities. Researchers at the University of Oxford used such criteria to estimate the automation probability of 702 occupations, including 14 representative roles in maritime transport. While many of these roles are not unique to shipping and the data reflects U.S. conditions, useful patterns emerge. Jobs in maritime services—such as insurance underwriters, brokers, and agents—are especially vulnerable because their tasks often involve structured information retrieval and standardized processes, which are easier to automate. Port operations are also more likely to be automated than shipboard activities. Interestingly, engineering officers on ships appear less susceptible to automation than bridge officers like captains or mates, mainly because current propulsion systems are not yet fully electrified, making automation of engineering functions more complex. However, as technology evolves rapidly, even tasks considered difficult to automate today may become automatable in the near future.

Operational Impact
A major operational concern with maritime automation is the vulnerability of digital systems to technical failures and cyber threats. Due to the interconnected nature of digital networks, a single malfunction can lead to widespread disruption. However, these risks can be reduced through robust preventative measures and cybersecurity protocols, as practiced by leading technology firms. Standards such as ISO/IEC 27001 have been developed to support the enhancement and ongoing maintenance of information security management systems in organizations.

Technical Impact
As the maritime sector becomes increasingly digitalised, a technological gap may emerge. In the traditional shipping environment, skills and expertise were often gained through formal training as well as hands-on experience. For many shipping companies in less-developed regions, operating advanced ships and equipment has been manageable. In a fully digitalised context, however, the creation, management, and upgrading of new transport systems will present a significant challenge. It is crucial that all maritime organizations—regardless of size—prepare for this shift, adapt accordingly, and become proficient with new technologies. Experience has shown that artificial intelligence can be implemented flexibly to address both broad and specific maritime challenges.

Legal and Regulatory Impact
The rise of autonomous ships introduces numerous legal and regulatory challenges. Under existing international frameworks such as those of the IMO, manned operation is a core requirement. Almost all maritime regulations and contracts assume crew presence, with specific responsibilities assigned to shipmasters under conventions like SOLAS and COLREG. Legal concerns extend beyond manning to include jurisdiction, shipbuilding standards, navigation safety, environmental compliance, and marine insurance. Recognizing these issues, the global maritime community has started to act. In 2018, the IMO formed the Maritime Autonomous Surface Ships (MASS) working group, composed of 33 Member States, 1 Associate Member, and 17 observers from NGOs and IGOs. The group’s goal is to review and enhance existing regulatory instruments to support safe and secure autonomous shipping. A report on the implications of MASS for ten IMO safety and security conventions was submitted at the MSC-100 meeting.

Overall, the impacts of maritime automation are interrelated but distinct. Economic forces serve as the main drivers of automation, while social and operational outcomes are consequences, and technical and legal factors act as key enablers. In summary: economics initiates the push, technology and regulations make it possible, and social and operational changes reflect its effects.

 

 

Harnessing Big Data, AI, and the Evolving Landscape of Maritime Risk

In the maritime industry, a company’s ability to manage risk plays a decisive role in determining its success or failure. While this is true for many sectors, shipping is particularly exposed to risk, given its operational complexities and market volatility. Maritime risks fall into two broad categories:

1. Commercial (market-related) risks
2. Technical (operational) risks

Market risks stem from fluctuations in freight rates and the financial exposure tied to high-value assets like ships. Operational risks involve safety hazards affecting ships, crew, and third parties. The rise of digitalisation and artificial intelligence (AI) introduces new capabilities that allow organisations to better understand and manage these risks. Beyond cost savings, the key benefits of automation and AI lie in improved predictability, enhanced decision-making, and the potential to reshape maritime transport at a fundamental level.

The Role of Big Data and AI in Reducing Market-Driven Maritime Risks

Market-related risks in shipping are closely linked to the unpredictability of freight markets and the reliability of business partners. At the core of this uncertainty is incomplete information and unclear relationships between data points. Making informed decisions—such as whether to invest in a new bulk carrier—requires comprehensive data across a wide range of variables. This includes demand forecasts, fleet supply, competitive dynamics, economic policies, demographic trends, shipbuilding capabilities, financing conditions, and internal organisational factors.

The sheer breadth and depth of this information make it difficult for most companies to capture and assess all necessary data, leading to decisions based on partial knowledge. This data gap represents a primary source of market risk. Similarly, credit risks arise when there is inadequate information about the financial health and reliability of stakeholders such as customers, suppliers, or partners.

Effectively managing these risks requires not just access to data but also the analytical tools to interpret it correctly. Traditionally, decision-making has relied on internal experience from managers and external insights from brokers and consultants. However, such experience is inherently subjective and influenced by individual judgement, background, and even personal biases. This can result in inconsistent outcomes—one reason why strategic decisions often shift dramatically when a company’s leadership changes.

The quality of maritime decision-making frequently hinges on a shipowner’s ability to process available information and anticipate future developments. When experience alone fails to uncover critical insights, risk increases. These limitations—data scarcity and subjective interpretation—contribute to persistently high levels of market-related maritime risk. Big data and AI offer a solution by enabling more comprehensive data collection and objective, algorithm-driven analysis, paving the way for more accurate and consistent decision-making in an increasingly complex maritime environment.

Big data and artificial intelligence (AI) are significantly reshaping how maritime risks are understood and managed. With the increasing availability of market data in digital form and the digitisation of internal operations, advanced analytics tools like machine learning, combined with strong computing capabilities, now allow the extraction of previously hidden insights, patterns, and answers from large datasets.

In 2019, a Japanese shipping firm initiated a collaboration to use AI and data analysis for developing highly accurate predictive models in maritime logistics and market conditions. Below are examples that demonstrate these developments and highlight key considerations.

Marine Insurance Applications

Marine insurance, which provides protection against potential losses to ships, cargo, or third parties, relies heavily on accurate risk evaluation. Ideally, underwriters would have access to comprehensive data on ships, operators, cargo types, trading areas, and historical records.

In practice, however, they often work with limited and fragmented data, such as ship registry details, class, or past deficiencies. Internally, valuable information from claims departments may take time to reach underwriting teams. Yet, a wide range of other relevant data exists—such as AIS (Automatic Identification System) records showing real-time and historical ship movements—which remains underutilised.

Some insurers are now building far more comprehensive datasets, integrating information on ship profiles, maintenance and safety histories, navigational behavior, and port visits. Using machine learning, they can model and predict risks like accidents, cargo loss, delays, or congestion more accurately. These AI-driven tools not only enhance risk evaluation and pricing but also support proactive risk management. As more stakeholders contribute to shared “InsurTech” platforms, the models improve, and predictions become increasingly precise. Sharing past claims data, for instance, could lead to the creation of even more accurate risk assessments.

Blockchain and Transaction Risk Reduction

In maritime trade, credit risk is another major concern, especially given the complexity of transactions involving many parties. Traditional documentation methods, based on paper, are slow, expensive, and vulnerable to fraud.

Blockchain technology offers a transformative solution by creating a secure, distributed digital ledger that records and verifies transactions among all parties without intermediaries. Whether representing a ship, cargo, bill of lading, or payment, each asset can be traced transparently and securely. Blockchain systems reduce administrative overhead, boost security, eliminate fraud risks, and provide full auditability. According to a PwC survey, 84% of global organisations are already exploring or using blockchain. The maritime sector has begun adopting blockchain in areas ranging from ship finance and classification to port operations and logistics.

Most blockchain systems in shipping are permissioned and private, unlike public systems. These networks are typically established by a lead organisation or consortium that controls access and governance. Private networks offer increased privacy and require less computational power. Maritime supply chain blockchains bring together stakeholders such as shippers, freight forwarders, customs authorities, banks, insurers, and ports. However, for these systems to work effectively, issues like legal standards, norms, and dispute resolution frameworks must be addressed. Although the path to full implementation is complex, the long-term benefits in terms of trust, efficiency, and risk reduction make blockchain a promising tool for managing market-related maritime risks.

 

 

 

How can big data and AI help mitigate operational risks in maritime transport?

A substantial portion of maritime risk is associated with ship operations and navigational safety. Although maritime safety has advanced significantly over the past 50 years, accidents and incidents still occur frequently, with thousands of casualties reported annually. This ongoing exposure is reflected in global marine insurance premiums, which remain around US$30 billion per year. Common causes of operational incidents include grounding, fire or explosion, flooding, collision, and machinery failure. These risks can be assessed across three key dimensions: navigational safety, system reliability, and regulatory compliance.

● Navigational Safety: According to updated data from the marine insurance sector, over 50% of total vessel losses recorded through 2024 were due to foundering, often resulting from grounding and severe weather conditions. By continuously monitoring variables such as sea state, meteorological data, ship location, speed, and electronic navigational chart (ENC) inputs in real time—and comparing these with established safety thresholds—anomalies and threats can be identified early, allowing timely alerts and interventions. This enhances voyage planning, route optimisation, and collision avoidance. Current technologies already offer capabilities for calculating optimal routes and scheduling safe passage windows. For instance, maintaining proper under-keel clearance and adhering to COLREG rules regarding ship encounters can now be digitally managed. A comprehensive 2024 analysis of 693 accident investigation reports from six major maritime nations confirmed that collision and grounding remain the most prevalent incident types, with human error consistently cited as the leading cause. Failures in risk assessment, poor communication, misjudgment, and inadequate lookout were among the most frequent factors. Leveraging digital technologies, these risks can be significantly reduced. Using predictive analytics fed by weather, regulatory, AIS, and GPS data, safer and more economical routes can be computed, then benchmarked against historical voyage patterns. Anticipated vessel trajectories allow the generation of recommended manoeuvres for ship and shore-based operators. If deviations, erratic behaviour, or imminent risks are detected, automated alerts and guidance ensure timely responses—even autonomously, when applicable.

● System Reliability: Although mechanical and equipment failures are less common in modern shipping, technical faults still accounted for approximately 11.5% of maritime incidents in 2024. Technologies such as the Internet of Things (IoT) now enable real-time monitoring of onboard systems through smart, sensor-equipped devices. These devices transmit data to cloud or edge computing platforms, where machine learning is used to detect performance anomalies. For example, irregularities in engine pressure readings can signal mechanical issues in their early stages. This approach enables predictive maintenance, minimising downtime and reducing the likelihood of breakdowns. Additionally, visual and acoustic data captured via onboard cameras and microphones can be analysed with image and sound recognition tools. This enables classification societies to perform remote inspections, identify early signs of corrosion, and assess structural integrity—ensuring timely interventions and better maintenance planning.

● Compliance: Flag states are responsible for enforcing the international maritime conventions they adopt. However, many countries lack the expertise and resources to ensure effective implementation. A major challenge in global maritime safety and environmental protection is the shortage of qualified ship surveyors. Here, AI, blockchain, and digital technologies offer transformative potential. For instance, blockchain can address issues such as misdeclared cargo—implicated in nearly 25% of container ship incidents—by securing and verifying cargo data throughout the logistics chain. Technologies already in use for maintenance, insurance, documentation, and classification can also support compliance monitoring by flag states. These innovations improve the efficiency and accuracy of inspections and enforcement processes.

In summary, AI-driven maritime risk mitigation relies on digitised data made available through IoT systems and business digitalisation. Blockchain and AI stand out among digital technologies for their direct impact on reducing risk, while other tools contribute indirectly. With proper implementation, these technologies can transform maritime safety, system reliability, and regulatory enforcement.

 

 

 

Competition from Trade Integration for Customer Control

While much of the disruption in maritime transport stems from advances in digital technologies within the industry, external forces are also reshaping the sector. One of the most prominent external disruptors is e-commerce, whose rapid growth is poised to significantly influence the future of international shipping. This section explores how the integration of trade and transport may evolve, the factors driving this convergence, and the potential leaders of this transformation.

Why Was Shipping Historically Separated from Trade?

In the past, shipping was closely intertwined with trade—traders often owned ships, and shipmasters directly participated in negotiations with buyers and sellers. Over time, however, maritime transport became a specialised, third-party service due to several key developments. Likewise, financial transactions in trade shifted from being handled by traders to banks. The very forces that caused this separation are now being challenged by digital advancements, particularly those enabled by the internet. Let’s examine these changes:

• Economies of Scale: One of the main reasons for the split between shipping and trade was the push for greater efficiency through larger operations. As trade expanded and competition intensified, only large carriers operating big ships could maintain competitive transport costs. Smaller traders were compelled to abandon their own fleets and rely on common carriers. The same logic led to other specialised services—such as bunkering and agency—being separated from core shipping functions. However, with digital technologies and the rise of autonomous ships, the cost benefits associated with large-scale operations, particularly those tied to crew expenses, are being eroded.
• Specialisation: As the maritime industry evolved, it grew increasingly complex, requiring deep technical, regulatory, and operational knowledge. Trading companies no longer had the capacity to manage shipping independently. However, as digitalisation transforms the sector, processes are becoming more streamlined and automated, making it feasible for shipping to once again become an integrated part of trade.
• Advancements in Communication: Historically, shipmasters acted as trader representatives out of necessity, as real-time communication was limited. The separation between trade and transport became viable once importers and exporters could coordinate remotely. With today’s interconnected world and the ubiquity of satellite communication, full visibility and control are possible regardless of location.

Although the separation of shipping from trade helped to lower costs and improve efficiency, it has also introduced new challenges. Traders now must actively manage transportation logistics alongside market dynamics, and in some cases—such as in commodity trades—freight rates can exceed the value of the cargo itself. In these scenarios, logistics can determine the profitability of a transaction. The growing unpredictability of transport costs has become a significant risk for traders. Digitalisation presents a promising solution by offering integrated systems that streamline trade and transport, reduce complexity, and return greater control to the customer.

 

 

Why are customer interfaces and data central to supply chain control?

In the next decade, the most significant disruption to maritime transport may not stem from within the shipping industry through automation or new operational models, but rather from external forces that could sever the long-standing link between shipping companies and their core clients—importers and exporters.

Maritime transport risks being redefined as a supporting element within broader trade ecosystems, much like packaging is today. One major driver of this shift is the emergence of the “platform economy,” which has already transformed industries such as retail, finance, hospitality, and urban mobility. These tech-driven companies disrupted conventional sectors not by offering superior products or services, but by capturing the most valuable part of the transaction—the interface with the customer—through digital platforms that radically improve user experience. Their success lies in providing unmatched speed, convenience, transparency, security, and integration, which has redefined customer expectations and loyalty. The result is twofold: platform providers take over the customer interface, and they gain control of the transaction data. This “decoupling” has profound implications for traditional service providers. In the digital age, access to customer data is an essential competitive asset. It informs product development, pricing, customer engagement, and strategic positioning.

As digitalisation and AI progress, the ability to control and analyse this data becomes a decisive advantage. Traditionally, shipping lines maintained direct links with their customers, even in the presence of intermediaries. However, as more transactions shift online and data becomes centralized on digital platforms, these connections risk being eroded, posing new challenges for maritime transport providers.

 

Who are the most likely disruptors of the shipping industry?

E-commerce giants are the most likely candidates to disrupt global shipping. These companies have already redefined retail and wholesale logistics using digital platforms and are now extending their reach into cross-border trade. Their ambition is to integrate every aspect of the trading process—including financing, customs clearance, logistics, warehousing, port services, and ocean shipping—into a seamless, end-to-end service. Customers could initiate and complete entire international transactions with a single click and one payment. AI and digitalisation allow these companies to reassemble the fragmented global trade process into integrated digital ecosystems without sacrificing the benefits of specialization. This level of vertical integration is financially and technically beyond the reach of even the largest shipping companies.

While some carriers have tried to create their own e-platforms, these remain focused on transport logistics rather than full trade integration. As comprehensive trade platforms gain traction, importers and exporters are more likely to adopt them due to the clear value they offer. Two key consequences may emerge. First, e-commerce firms could dominate global trade flows, reducing shipping companies to subcontracted port-to-port carriers. Even if shipping remains outsourced, direct relationships with importers and exporters may be lost, with e-commerce platforms becoming the primary clients. Second, many traditional shipping intermediaries—such as shipbrokers, agents, and freight forwarders—could be displaced. As digital platforms absorb and automate their functions, services like marine insurance and ship classification may also become part of integrated trade ecosystems, reshaping the structure and function of the maritime industry.

 

The Way Ahead for Maritime Transport: From Digitisation to Digitalisation and Full Digital Transformation

We have explored the digital technologies that could fundamentally alter maritime transport and drive a complete transformation of the shipping industry. Despite these developments, significant uncertainties remain. Some argue that the capabilities of artificial intelligence have been overstated. A widely cited milestone is the emergence of ChatGPT, developed by OpenAI, which demonstrated an unprecedented ability to generate human-like text, answer complex questions, and assist in a wide range of professional and creative tasks. While impressive, critics point out that such language-based applications may not directly compare to the technical and operational complexities involved in running and automating ships.

To assess the future of the shipping industry, we must address four key questions: Will the shipping sector be digitalised and its current business model disrupted? If so, when is this likely to happen, and how deep will the transformation go? What will drive this change? And how should industry players respond?

We will examine these questions by focusing on two major challenges posed by disruptive digital technologies. The first is the prospect of widespread automation across maritime operations, representing internal and revolutionary shifts within the industry. The second involves the convergence of trade and transport, highlighting external disruptive forces. While it is difficult to predict exact outcomes or timelines, especially with digitalisation still in progress, our analysis will rely on underlying structural dynamics rather than speculative forecasts or assumptions about specific companies or technologies leading the way.

 

 

 

Why will most maritime transport activities be digitalised and automated?

Although maritime transport—particularly ship operations—is inherently complex and varies significantly across different ships, this complexity does not preclude the potential for automation. Despite the uniqueness of individual ships, their shared technical and operational characteristics are sufficient for AI-powered systems to learn, adapt, and function effectively. Several core reasons support the likelihood that maritime transport will undergo large-scale digitalisation and automation. Among these, three stand out for highlighting the advantages of AI-based systems over traditional human-led decision-making.

● Comprehensive data collection:
The effectiveness of decisions—whether made on board or ashore—largely depends on access to complete and relevant data. In many cases, suboptimal decisions arise from gaps in available information. Digitalisation captures data that would otherwise be lost and, when expanded to cover internal operations, external conditions, and environmental factors, greatly enhances the possibility of uncovering key insights. For instance, voyage planning becomes far more accurate when it incorporates full data sets on weather patterns, sea conditions, ship performance, fuel consumption, cargo status, and port operations. Similarly, marine insurers can improve underwriting accuracy by analysing operational behavior data, rather than relying solely on static records or historical claims.

● Superior data processing and learning capacity:
Digital technologies have progressed rapidly, allowing sensors and AI systems to perceive and interpret the physical environment with remarkable accuracy. These systems can gather and analyse data at a speed and scale that far exceed human capabilities. Moreover, the computing power and machine learning techniques underpinning AI systems are now able to generate insights and predictions that rival—and often surpass—those of seasoned human experts. Like a veteran seafarer who draws on years of experience, AI systems can store, recall, and process vast volumes of information. But unlike humans, they are not constrained by memory limits or a finite career span. ChatGPT, for example, demonstrates how advanced AI can produce knowledge-based outputs informed by a massive and continually growing data set, revealing patterns that might otherwise remain hidden.

● Precision and relevance in data usage:
AI systems not only handle massive datasets efficiently but also identify and focus on the most critical variables. Through sophisticated algorithms and data-mining capabilities, they uncover meaningful relationships and predictive patterns that humans might miss. This renders expert-based models less effective, as human analysis is often limited by cognitive capacity and subjective bias. For example, a voyage plan created by the most experienced shipmaster may still be inferior to one generated by an AI system drawing on comprehensive, real-time global data. Similarly, an AI-driven risk assessment could outperform traditional underwriting decisions by identifying hidden indicators of operational or financial risk.

The combined strength of AI in collecting, processing, and applying data highlights the existence of a “dark knowledge” layer—insights and optimal solutions that humans have yet to uncover. Much like ChatGPT’s ability to produce informed responses across a wide range of domains using vast and complex data, AI in shipping can reveal operational best practices previously unknown or inaccessible. These solutions may lie outside the limits of current human expertise, but digitalisation offers the tools to access and apply them.

That said, in areas driven by competitive advantage—such as market strategies or pricing—AI may not offer the same edge if all players adopt similar systems, as any advantage becomes relative. However, in domains focused on safety, maintenance, risk management, and operational efficiency, the shift toward AI and automation is poised to be both disruptive and transformative.

 

 

What is the timeline for digital transformation in shipping?

Major technological shifts typically unfold over extended periods. However, with the rapid advancement of technology, intensifying global competition, and increasingly interconnected systems, the time required for new technologies to replace older ones is consistently shrinking. Historically, it took nearly a century for steamships to fully replace sailing ships in international trade. Containerisation, introduced in the 1950s, required around 50 years to capture roughly 75% of the international general cargo market. By contrast, the widespread adoption of smartphones, which emerged in the late 2000s, disrupted numerous industries—such as photography, music, banking, and news media—within just a decade. Similarly, electric and autonomous vehicles are projected to become mainstream more quickly than past technological revolutions.

Predicting when autonomous ships will become the standard remains difficult. For one, ships constructed today are not autonomous and typically have an economic lifespan of about 25 years. Additionally, digital technologies are still evolving. While new innovations applicable to shipping continue to emerge, there are also outstanding technical challenges to full digital integration. Furthermore, if the benefits of digitalisation are not equitably shared, short-term disruptions may trigger political and social pushback, which could decelerate progress.

Despite these uncertainties, the digital shift is clearly underway and likely to gain momentum. By around 2030, most maritime transport functions in advanced economies are expected to be digitised, supported by mature AI, blockchain, electrification, and communication technologies.

 

 

What are the main impacts of digital transformation on maritime transport?

Experience shows that the pace and depth of change are shaped more by the societal and institutional capacity to adapt than by the readiness of technology itself. The digital transformation of maritime transport will have broad and deep implications. It will alter employment structures, change working conditions, and potentially displace workers. The success of this transition depends heavily on how well companies manage organisational change and social resistance. Additional challenges relate to data governance and system security.

• Employment: One of the most significant challenges to digital transformation is the potential loss of jobs. This is a societal issue that must be addressed through coordinated efforts by individuals, businesses, and governments. As in past technological disruptions, new jobs will be created as others are phased out—though often in different sectors such as health or education. Maritime transport is likely to face a considerable contraction in its labour force.The impact on employment will vary geographically and across professions. Seafarers, who are recruited internationally, will be affected differently from dockworkers, who are locally employed. According to 2024 estimates, the number of seafarers supporting international shipping remains substantial, with countries such as the Philippines continuing to supply much of this workforce. Meanwhile, automation in ports is expected to significantly reduce local dockworker positions. A key aspect of mitigating the impact is ensuring that the benefits of digitalisation are equitably shared. Because the costs of transition are immediate while the benefits accrue over time, governments and broader society must support reskilling and job reintegration initiatives to enable a fair and sustainable transformation.
• Data issues: In the digital economy, data is arguably the most valuable asset. In maritime transport, two primary data challenges exist: a large volume of data remains uncollected, and much of the data that is available is underutilised. Full digitalisation and automation of maritime processes are necessary to unlock the potential of data. The shipping industry is still in the early stages of this transformation, and policy discussions among governments, industry stakeholders, and consumers are needed to resolve critical issues. These include data ownership, privacy, access, sharing, commercial sensitivity, and cross-border data governance.
• System reliability and cybersecurity: No digital system is entirely immune to breakdowns or cyberattacks. Reliability and security must be managed within a comprehensive risk framework. While digital systems may experience fewer disruptions, the potential severity of failures can increase. Consequently, the risks of digital systems are sometimes overstated. Nonetheless, maritime transport can draw from best practices in other industries, including robust legal protections, effective cybersecurity policies, technical redundancies, and ongoing staff training, to maintain system integrity and resilience.

 

 

 

Who will lead the digital transformation in maritime transport?

Most companies engaged in maritime transport now acknowledge that digitalisation will reshape their industry and that transformation is necessary. However, while some have taken decisive steps, many are still unsure of where to begin or how to navigate the digital landscape.

A few leading firms in shipping have made tangible progress, but numerous others remain hesitant, daunted by unfamiliar technology concepts and uncertain about which innovations to pursue. Some industry participants continue to adopt a cautious “wait and see” stance, citing historical patterns in which early adopters of new technologies did not always become long-term market leaders.

Indeed, the early stages of trial-and-error innovation can be risky and expensive, and following later might avoid those costs. However, in this digital era, being a technology front-runner offers a distinct advantage—especially through early access to operational and customer data. This access creates a feedback loop, allowing these pioneers to refine their services continuously, strengthen customer retention, and widen the gap over competitors. In this context, prolonged inaction may carry significant consequences once data-driven competition intensifies.

The container revolution remains the most pivotal innovation in modern liner shipping, yet it originated outside the maritime sector—from a trucking executive who redefined global trade. A similar pattern could emerge in the digital transformation of maritime transport. In marine insurance, for instance, many InsurTech leaders are not legacy firms but tech startups founded after 2010. Across industries, the key disruptors in the digital age have often been new entrants rather than established players. For example, Apple transformed personal entertainment and smartphones, Revolut reshaped digital banking, Canva redefined graphic design accessibility, Bolt disrupted urban mobility in Europe, and Shopify revolutionised e-commerce for small businesses.

Why do digital pioneers so often come from outside the industries they disrupt? There are two main reasons. First, digital transformation effectively resets the playing field. Traditional advantages like market share, scale, and decades of experience lose their edge, and sometimes become burdens. This reset allowed companies like BYD to challenge traditional automakers. Second, success in the digital economy relies more on mastery of data and technology than on long-standing sector expertise—an area where new entrants often have the upper hand. Since the 2010s, a new generation of data-driven startups has emerged that can convert raw machine data into actionable business intelligence through algorithms and analytics. The future leaders in smart shipping are likely to share the following traits:

● They consistently identify and deliver previously unmet customer needs—such as real-time financial risk scoring, major reductions in fraud, significant drops in navigational and technical incidents, paperless workflows, and instant, verified payments.
● They separate the customer interface from the core service, repackage it with added value, and seize control of transaction-critical data. In shipping, examples include integrated logistics initiatives from companies like JD Logistics or Coupang, which are building streamlined trade ecosystems that include shipping.
● They rapidly develop and deploy digital capabilities, harnessing the full potential of technologies such as AI, blockchain, and IoT to create new business models. InsurTech startups that use predictive analytics, blockchain-based freight verification platforms, or smart maintenance systems for ships exemplify this trend.

While today’s shipping companies may possess the capital, networks, and know-how to lead the digital transformation, they face strong competition from agile newcomers with no legacy constraints. Digital success now hinges more on technological innovation than on maritime tradition. New entrants—often more open to experimentation and faster to act—have less to lose and more flexibility to pursue radical change. These attributes are critical to driving the kind of disruptive transformation that the shipping industry increasingly requires. So far, many traditional maritime players have yet to fully commit to bold investments in digital technologies, leaving space for emerging leaders to shape the industry’s future.

 

 

 

What are the principles for a successful maritime digital transformation?

The impending wave of digitalisation is poised to reshape economies and societies just as previous technological revolutions have done, and maritime transport will be no exception. The shipping industry will undergo fundamental restructuring, and the future success of each shipping company hinges on the actions it takes today in response to digital challenges. While investing in people and technology, crafting long-term strategies, and making bold organisational changes are essential, the most critical factor is ensuring the correct strategic direction. Drawing from experiences in other industries and the specific characteristics of digital disruption, five core principles emerge—areas where many maritime organisations are especially prone to missteps.

● The focus should be on solving problems, not choosing technologies.
Buzzwords like blockchain, 5G, big data, machine learning, AI, IoT, data mining, and cloud computing can overwhelm shipping professionals. Though there’s growing awareness of the need to embrace change, many companies mistakenly believe that selecting the right technology is the starting point for digitalisation. In reality, the transformation is not primarily technological but customer-driven—customers will ultimately dictate change by adopting new, higher-value services made possible by technology. Technology is merely the tool; the goal is to solve fundamental problems and create new customer value. Solutions should target major bottlenecks or unmet needs with bold, transformative approaches, not incremental fixes. A historical example is containerisation, which emerged not from improving existing cargo-handling methods, but from reimagining the process entirely. Today, similar breakthroughs can be achieved through digital technologies and AI—but only if the transformation begins with identifying core customer problems and developing radical solutions to address them.

● The focus should be on value creation, not cost reduction.
Although most shipping companies operate under significant cost pressure, digital transformation should not be viewed merely as a tool for cutting expenses. While cost is important, the primary aim should be the creation of new value for customers. Competing solely on price limits long-term growth, while technologies like AI and automation can deliver transformative benefits far beyond savings. For example, using AI and big data to automate credit evaluation in ship finance or risk assessment in marine insurance brings unprecedented accuracy and quality—results that were previously unattainable. Likewise, replacing crane operators in ports or watch officers at sea with automated systems offers more than just cost savings: it enhances safety, reduces human error, and improves service quality. Ultimately, the societal benefit lies in freeing people from hazardous and demanding work environments.

● The focus should shift from “improving operations” to “building new business models”.
Many shipping companies view AI and automation primarily as tools to enhance existing operations. While these technologies can certainly improve current workflows, that should not be the main objective. The true purpose of digitalisation is not to make existing systems better, but to enable entirely new business models. This is similar to how Amazon’s retail approach didn’t refine Walmart’s model—it redefined it. Likewise, initiatives like TradeLens, a blockchain collaboration between Maersk and IBM, aim not to enhance document processing, but to eliminate paper-based processes altogether, creating a secure and transparent system that transforms maritime trade.

Innovative business models emerge from companies that grasp the full potential of digital technologies to overhaul old systems and build new frameworks. These businesses think beyond conventional limits and use digital and AI-powered systems to deliver new value and improve the customer experience. Ultimately, it is not the shipping industry that will determine whether automation and digitalisation take hold, but the end users. The added value these technologies bring is too significant to ignore—companies that fail to adapt may not survive.

It is also essential to understand that automation, AI, and digitalisation are deeply interconnected. Port or ship operations cannot be automated without first being digitised, and to realise the full benefits of automation, AI must be leveraged. Conversely, once data-rich digital systems are in place, automation becomes a necessity—because no human can process and act on that volume of information as effectively or quickly as a machine can.

● The goal is no longer “getting cargo”, but “getting data”.
Traditionally, shipping companies have focused on securing more cargo or business. However, in the digital age, the central aim should be acquiring and utilising data. A company evaluating the benefits of digitalisation solely through the lens of cost-benefit in cargo transport may miss the bigger picture. Data has become the most vital resource of the 21st century.

There are three key reasons why data is crucial for the shipping industry. First, even well-run shipping companies operate with only a fraction of the data they truly need. Digitalisation unlocks access to essential internal and external information that can vastly improve decision-making and competitiveness. Second, the data generated in shipping is valuable not only for improving the industry itself but also for driving innovation and societal progress in areas like sustainability, logistics, and trade. Therefore, decisions about automation should not be based only on job costs but on long-term strategic value. Third, shipping companies share their customers with other players in the logistics and trade ecosystem. The one who owns the customer data ultimately controls customer relationships and the broader value chain.

● The challenge is less about “new technology” and more about “new leadership, organisation, and talent”.
While digital technologies are essential, they are not the hardest part of digital transformation. If technology is the hardware, then leadership, organisational structure, and workforce capability are the software—and these are what determine success. A digitally enabled shipping company requires a new mindset and a structure that supports automation and innovation. This transformation can mean job losses, new responsibilities, and the need for upskilling, which demands a committed leadership and a company-wide investment in people.

Leadership here means whether top executives—owners or CEOs—truly understand what’s at stake. Only with that understanding can they commit fully to the transformation. Investing in people means ensuring everyone in the organisation understands the importance of digitalisation, the risks of resisting change, and the benefits of embracing it. Clear communication, relevant training, and the selection of appropriate technologies are all essential to prepare the workforce for the future.

Though it will take time for digitalisation to reach its full potential, especially as AI and related technologies are still developing, the transformative impact on maritime transport will become increasingly visible in the near future as more companies progress along the digital path.

 

 

Summary

We explored the fundamental economic forces behind the disruptive changes currently facing maritime transport. While new digital technologies are the catalysts, it is ultimately customer demand for digital services—over traditional models—that is driving disruption. To grasp the true value of shipping from the customer’s viewpoint, we began by identifying the core value as the transport of cargo by ships. Around this core, we assessed the necessary supporting activities, resource inputs, and expected cash flows, which shape how each element is affected by digitalisation. Though cargo transport will continue in the future, it will be conducted in fundamentally different ways. We then evaluated the digitalisation and automation potential of major maritime activities. Some, like engine operations and cargo handling, are already highly computerised, while others—such as ship finance and marine insurance—remain largely analogue. We also considered the programmability of these activities, noting that tasks which are routine, repetitive, and standardised are more easily automated, although no process is ever truly without a standard. Historically, disruptive shifts have followed major technological breakthroughs.

We reviewed key developments in digital technology—focusing on data collection, transmission, processing, and application—driven by advances in computerisation, internet connectivity, sensors, and the Internet of Things. These were accompanied by major gains in data transfer and storage, as well as in computing power and algorithm sophistication. These technologies, still in early development stages, continue to evolve rapidly. We considered the future impact of automation and AI in maritime transport, stressing broader trends over specific forecasts. Starting with customer value creation through digitalisation, we compared current maritime service models with their potential future counterparts. A special focus was placed on automation, referencing an Oxford University study assessing the automatability of various maritime functions—identifying high potential in areas like marine insurance and cargo handling, and lower potential in ship finance and training. We also examined the implications of automation across economic, social, operational, technical, legal, and regulatory dimensions.

Shipping inherently involves both technical and commercial risks. We analysed how digitalisation and AI could help mitigate these risks, primarily by addressing uncertainty—often the result of insufficient data or poor data processing. Through technologies like big data, AI, blockchain, IoT, and predictive analytics, uncertainty can be significantly reduced, as seen in their successful application in ship finance, insurance, and preventative maintenance. A major challenge lies in the possibility that future market leaders may emerge from outside the traditional maritime sphere. Tech-driven entrants—such as those originating from e-commerce or start-ups—often start with specific niches like ship agency or marine insurance and may expand to integrate maritime transport into global trade ecosystems. While trade and shipping are currently distinct due to past advantages of specialisation and scale, digital technologies may enable reintegration. These newcomers are likely to control the customer interface and data while outsourcing actual shipping services to existing firms.

We focused on how maritime organisations must respond to these disruptions, emphasising three essential data-related strengths: broad data coverage, advanced processing, and effective utilisation. AI and automation surpass human capabilities across all three. As for when digitalised and automated maritime transport becomes the norm, we refrained from offering precise predictions, urging caution instead. Among the most serious consequences are potential job losses. Ensuring a fair distribution of the benefits and burdens across society is essential to a successful transition. Other key considerations include data privacy, ownership, accessibility, system reliability, and cyber security.

Future leaders in maritime digitalisation will be those who recognise the new customer value, separate the customer interface from other functions, and apply advanced digital technologies effectively. We concluded by correcting common misconceptions: digital transformation is not about “cost-saving” but “value creation”; not merely about improving operations but about building new business models; not about choosing technologies but about solving problems; not just about cargo but about data; and ultimately, not about technology alone but about people.

 

 

 

 

 

 

 

 

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