Large shipping companies are beginning to adopt tools based on artificial intelligence (AI) in their management models. This includes their transport activities, logistics planning, time management, stopovers, fuel consumption, ship maintenance, etc. In the race to streamline time and costs in an increasingly complex logistics chain, having AI can represent a qualitative leap in the planning of major shipping companies, providing a predictive way of operating, anticipating complex situations, and being able to foresee them in a satisfactory manner for the companies.
Typically, the company we analyze departs from Shanghai, making stops at ports in Taipei, Hong Kong, Macau, the Strait of Malacca, Singapore, Colombo (Sri Lanka), the Arabian Sea, the Gulf of Aden, the Bab-El-Mandeb Strait, the Red Sea, Cairo, the Suez Canal, the Mediterranean Sea, the Port of Algeciras, Sines, Portugal, Rotterdam, and Hamburg. A typical east-west route, for example, for the Chinese Silk Road. Current geopolitical circumstances and ongoing conflicts make such planning impossible.
The attacks by Houthi militias on ships in the Red Sea and the Persian Gulf are now extending even to the Gulf of Aden. Ships must plan new routes around the Cape of Good Hope, avoiding the Suez Canal.
Companies input all this data into their AI-based applications and tools. A route change with a significant increase in navigation miles means higher fuel consumption and increased CO2 emissions. The tool plans the new route, taking into account all technical, economic, and logistical variables through a complex algorithm. The itinerary change obviously implies higher costs.
Which ports of call will we need to complete this route in the best possible way? Optimal timing must be achieved, but data will be cross-referenced with real-time weather variables so that the navigation plan can be reconfigured if worsening conditions in South Africa, as has been occurring in recent months, are detected.
In which ports and at what price can we refuel with the necessary type of fuel, adjusting layover times and crew changes? These are more variables controlled by the system. And if we reach European ports, how will the payment of ETS for emissions affect our scale and final route costs? The program will consider this and propose alternatives if they are more viable. Customs tariffs, disruptions between competing countries delaying the introduction of products into competing markets, goods inspection services, potential dockworker strikes, climate change and its effects on port infrastructure—all these variables feed the AI system to leave no detail to chance.
Major Shipping Companies Embrace AI to Optimize Logistics, Reduce Costs, and Enhance Predictive Capabilities in a Complex Global Trade Environment
AI takes into account each of these variables, analyzing in real time the best possible travel options and avoiding any type of obstacle. From all perspectives. It’s an anticipatory work addressing all possible problems that wasn’t possible until now.
Decisions will be made based on real data that aligns with reality, adapting the travel plan to any type of disruption. The goal is unprecedented optimization, but also a more efficient, sustainable, faster service and customer satisfaction through predictive technology.
In this scenario, port promotion as we knew it no longer makes sense. Traditional commercial activities will not attract traffic to one port or another. If AI provides the keys to the most efficient routes, port commercial strategies will have to be reinvented. The key lies in digitization on a much broader, transversal scale, introducing new management modalities. Inter-port collaborations, technology alignment and exchange, information dissemination methods, entity transparency, Smart Ports groupings, Port Community Systems (PCS), 5G technology, and the plurality and quality of port services, etc.
The speed and ease with which each port facility can position its data on the network is directly proportional to its success in attracting traffic and being considered in the calculations and forecasts of AI systems. This represents a radical change in port strategy, with collaborating port groups playing a crucial role in linking their working methods and attracting traffic by offering the best services in a coordinated manner. All under a highly advanced and cutting-edge digitalization framework.
This marks a new era for port management with significant transformative concepts, where control over ships, their cargo, and its traceability will increase daily. This will result in cost adjustments for companies and greater competitiveness among shipowners. These changes will energize major charter groups with the means to make this qualitative leap, demanding much more from port facilities to avoid falling behind.
On the other hand, ongoing geopolitical conflicts are shifting production centers and logistics chains to other countries and centers with greater stability, capable of competing with China in terms of price and productivity. India, Pakistan, Indonesia, the Philippines, Malaysia, Singapore, Thailand, Vietnam, Brunei Darussalam, Cambodia, Laos, and Myanmar are working intensely to tilt Asia’s productive centers. Export ports associated with these new aspiring global manufacturers are already placing technology at the forefront of their strategy. In this strategy, information and data will be of paramount importance as they will allow dominance in markets.
Ports like Singapore, a permanent example of resilience, use technologies like machine learning to optimize ship arrivals and docking in very congested facilities with limited space. At the same time, stevedoring and concession companies use Just-in-Time logistics platforms to respond to more customers and operations in congested spaces.
In ports with permanent traffic congestion and access issues like Los Angeles, shippers have digital infrastructures to provide information to all involved agents simultaneously and in real time, avoiding congestion and costly waiting times. The port of Quebec uses AI to calculate traffic volumes before the ship’s arrival and, depending on the cargo to be unloaded, the necessary means for it.
But all advanced ports agree on a collaborative formula. The reason is simple. If data is shared, efficiency will increase from origin to intermediate stops to the final destination, encompassing the entire port community, and these facilities will attract most of the traffic for obvious reasons.
All these reasons necessitate changing the conventional promotional model for a port facility transformation strategy. It’s crucial to remember that in this chess game, the pieces modernize quickly, as fast as technology advances, to keep playing. It’s a frenetic race that must be joined to compete in the major port leagues worldwide, stay on the map of routes defined by AI, and not arrive late to the future.
