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From Tracking to Predicting: How Artificial Intelligence Is Redefining Global Logistics
Updated: Sep 18
Industry Insight | September 2026
For decades, logistics was largely about answering one question:
Where is my shipment?
Artificial intelligence is beginning to change the question.
Increasingly, businesses want to know:
What is likely to happen next — and what should we do about it?
That distinction may define the next generation of global logistics.
Artificial intelligence is moving beyond experimental applications and becoming part of real supply-chain operations. Gartner identifies agentic AI and physical AI among the leading supply-chain technology trends of 2026, reflecting a wider movement toward systems capable not only of analysing information, but increasingly of recommending and executing actions.
For importers, logistics providers and businesses operating across international markets, the result could be a fundamental transition:
from reactive logistics to predictive logistics.
The Problem With Traditional Tracking
Traditional shipment tracking is extremely useful.
But in many cases, it tells a business what has already happened.
A container departed.
A shipment reached a port.
Customs clearance began.
A delivery was delayed.
That information creates visibility, but visibility alone does not necessarily provide enough time to act.
The next generation of logistics technology is attempting to move one step further.
Instead of simply reporting a delay, AI systems can analyse multiple data sources and attempt to identify disruption before it materially affects a shipment.
Weather conditions.
Port congestion.
Transportation patterns.
Historical transit times.
Supplier performance.
Inventory requirements.
Customs information.
Transport capacity.
Market demand.
AI can process these signals simultaneously, allowing logistics teams to identify patterns that would be difficult for an individual operator to monitor manually.
DHL's current logistics research places AI at the top of the technology clusters expected to influence supply chains, with advanced analytics and generative AI among the areas receiving significant attention from businesses planning future logistics investment.
The implication is significant.
The logistics industry is gradually moving from:
Track → Report → React
toward:
Analyse → Predict → Act.
Visibility Is Becoming Predictive
The commercial demand for this transition is already becoming visible.
A 2026 Maersk survey of North American supply-chain executives found that approximately 69% identified end-to-end supply-chain visibility as a priority area for AI and automation investment by lead logistics providers.
Around 54% identified advanced analytics and decision support, while 49% highlighted shipment execution management.
Supplier and vendor management was also identified as an important application.
Although the survey covered a relatively small group of Maersk customers in the United States and Canada, the results illustrate a wider change in expectations.
Businesses increasingly do not simply want access to information.
They want information that helps them make decisions.
That difference is important.
Knowing that a shipment will arrive late creates awareness.
Knowing several days earlier that it is likely to arrive late creates options.
A business may be able to reorganise inventory.
Inform customers.
Change transport arrangements.
Adjust production.
Redirect stock.
Reconsider purchasing.
Or prioritise another supplier.
In global trade, additional information is useful.
Additional time to make a decision can be considerably more valuable.
AI Could Change Route Planning Completely
International logistics networks contain thousands of variables.
A route that appears optimal when a shipment leaves its origin may no longer be optimal several days later.
Port congestion can change.
Weather systems develop.
Transportation capacity becomes constrained.
Political events can affect borders or shipping lanes.
Air and ocean freight prices move.
Artificial intelligence makes it possible to continuously reassess some of these variables rather than relying exclusively on predetermined logistics plans.
DHL describes AI-enabled logistics systems capable of detecting factors such as traffic, severe weather and port disruptions and using that information to support shipment rerouting and autonomous decision-making.
This does not mean human logistics expertise becomes irrelevant.
Quite the opposite.
AI can process enormous quantities of information.
Experienced logistics professionals understand the commercial consequences of that information.
The strongest future model may therefore not be human versus machine.
It may be:
Human expertise + artificial intelligence.
Technology identifies the risk.
Experienced professionals understand the transaction.
Together, they determine the appropriate response.
Smarter Forecasting Means Smarter Inventory
One of the most significant potential applications of AI occurs before transportation even begins.
Inventory has always required businesses to balance two competing risks.
Too little stock creates shortages and lost sales.
Too much stock locks valuable capital into products sitting in warehouses.
For import-dependent companies, that calculation becomes even more complex because replenishment may involve weeks or months of production and transportation.
AI-powered demand forecasting can analyse historical orders alongside wider datasets and identify patterns that traditional forecasting models may overlook.
IBM describes modern AI supply-chain systems as using large datasets and predictive capabilities to support forecasting, risk management, optimisation and real-time decision-making.
Better forecasting can therefore influence much more than warehouse management.
It can influence purchasing.
Supplier orders.
Transport requirements.
Financing requirements.
Working capital.
And ultimately profitability.
This is where the relationship between logistics and finance becomes particularly important.
Every Shipment Is Also a Financial Transaction
A shipment is not simply cargo moving between two locations.
It represents capital.
The company purchases goods.
A supplier needs to be paid.
Transportation must be organised.
Insurance may be required.
Customs and duties must be calculated.
Products remain in transit.
Only after delivery and eventual sale does the business fully convert that investment back into available cash.
The longer or less predictable that process becomes, the greater the potential pressure on working capital.
This means improvements in logistics intelligence can ultimately become improvements in financial management.
If a company understands its expected arrival dates more accurately, calculates landed costs correctly and gains clearer visibility over its international orders, it can make better decisions about cash requirements, inventory and future purchases.
The boundaries between logistics technology and financial planning are therefore becoming increasingly blurred.
AI Will Not Fix Bad Data
There is, however, an important reality behind the excitement surrounding artificial intelligence.
AI is only as useful as the information supporting it.
Gartner reported in January 2026 that 37% of logistics leaders were struggling to capture value from AI, highlighting digital maturity and AI-ready data as essential foundations for successful implementation.
This may be one of the most important lessons for businesses considering AI.
Companies do not become intelligent supply chains simply because they purchase an AI application.
Data must first be structured.
Systems must communicate.
Information must be accurate.
Processes must be measurable.
Suppliers and logistics providers must be integrated into the information flow.
Only then can sophisticated analytics become genuinely valuable.
For this reason, digitalisation remains one of the foundations of modern trade.
UN Trade and Development's Trade Digitalization Index 2025/2026, covering more than 170 economies, reflects the growing international emphasis on digital trade procedures and cross-border paperless trade.
AI may represent the next layer of intelligence.
But digital infrastructure remains the foundation beneath it.
From Digital Visibility to Intelligent Trade
This development is particularly relevant to the philosophy behind Eptagon Business Solutions.
EBS already approaches importing as an interconnected process rather than a collection of isolated services.
Through EBS Connect, clients can track orders in progress, access reporting relating to previous transactions, view account financial information and connect information from logistics providers within one digital environment. EBS describes the platform as part of a wider integrated import solution covering the process from supplier order through transportation and final delivery.
That distinction becomes increasingly important as international trade becomes more data-driven.
The future is unlikely to consist of separate systems for:
finance
purchasing
logistics
supplier management
shipment visibility
and business intelligence.
The direction of travel is toward connected ecosystems where information flows between each stage of the transaction.
AI can then transform that information into something more valuable:
decision intelligence.
Logistics Will Become Less About Movement and More About Decisions
Artificial intelligence will not eliminate ships.
It will not eliminate trucks.
It will not remove ports, warehouses, customs authorities or logistics professionals.
Goods will still physically need to move.
But the intelligence surrounding that movement is changing rapidly.
Tomorrow's competitive advantage may not simply come from transporting goods faster.
It may come from knowing:
what to order,
when to order it,
which supplier represents the lowest overall risk,
which route offers the strongest balance between cost and reliability,
how much working capital will be required,
and
what action should be taken before a disruption becomes a problem.
The physical supply chain will remain.
The intelligence controlling it will become increasingly sophisticated.
The Future Is Not Just Connected. It Is Predictive.
The first digital revolution gave businesses visibility.
They could see their orders.
Track their shipments.
Access their information.
The next revolution may give them something considerably more powerful.
Foresight.
Businesses that combine human expertise, reliable data, integrated systems and intelligent technology will be better positioned to navigate increasingly complicated international markets.
Because the future of logistics is not simply about knowing where your goods are today.
It is about understanding where your business needs to be tomorrow.
Eptagon Business Solutions
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