AI is evolving rapidly. New models and applications are emerging at an incredible pace. For logistics service providers, the opportunities are becoming increasingly practical – from processing orders and documents to supporting planning and data analysis.

With so many new solutions entering the market, it can be tempting to choose the best AI tool for each individual process. But adding more tools does not automatically make your operations smarter. The real question is: where can AI deliver value today, and is your technology landscape ready for what comes next?

The Next Step in Data-Driven Logistics

At Boltrics, we see AI as the next step in data-driven logistics. We distinguish between three levels: Personal AI, Hybrid AI, and Embedded AI. Personal AI helps individual employees search, analyze, and summarize information. Hybrid AI brings AI into day-to-day operations by connecting unstructured information, such as emails and PDFs, with structured data in your Warehouse Management System (WMS), Transport Management System (TMS), or Freight Forwarding System (FMS). This is where AI is already delivering practical value today.

From Email to Order Without Manual Data Entry

Take order processing. Many orders still arrive by email or PDF. Employees need to review the information, enter customer details, items, quantities, and delivery dates, and then manually create an order.AI can extract that information and convert it into structured data that can be processed directly in your WMS, TMS, or FMS.

At Boltrics, we combine this with master data validation, business logic, and exception handling. If information is missing or something does not add up, an employee can step in. This reduces manual data entry, speeds up processing, and lowers the risk of errors—while keeping exceptions visible and under control.

When AI Moves from Supporting to Acting

The next step is Embedded AI. Instead of simply supporting individual tasks or processes, AI becomes part of the system itself. Think of AI agents that identify exceptions, take action, or optimize processes across multiple steps.

For many critical logistics processes, we are not there yet. But the direction of travel is clear – and it raises an important question for logistics service providers today. As AI takes on more responsibility, can it rely on the data and processes underneath it?

If warehouse, transport, and forwarding data is spread across different systems, data is inconsistent, or every AI application requires another integration, scaling becomes increasingly difficult. Reliable automation requires reliable data. And without integration, scaling AI across your operations becomes much harder.

Avoid Adding Another Layer of IT Complexity

This is also why we take a critical view of the speed at which new AI tools are entering the market. One solution for order processing. Another for planning. Another for document analysis.
Each may deliver value on its own. But together, they can also add another layer of complexity to an already fragmented IT landscape.

For logistics service providers, that raises practical questions. Where does your customer and order data reside? Which applications have access to which information? How many integrations need to be maintained? And what happens when an AI model or technology provider changes?

That is why we believe AI should, wherever possible, become part of the platform your operations already run on. This allows you to introduce new capabilities without adding a separate data source, integration, and management layer for every new innovation.

More AI Requires More Control

An integrated foundation becomes even more important when AI moves beyond processing information and starts taking action. You need to be able to determine:

  • which information AI can access
  • which actions can be performed automatically
  • when human intervention is required
  • who, or what, made a change

and whether you can trace what happened afterward.

Data governance, access management, and security are therefore no longer just IT concerns. They become essential requirements for taking automation further across your logistics operations.

Build the Foundation, Then Accelerate

For logistics service providers, the opportunity is not about adding as many AI applications as possible. Start where AI can deliver clear value today – for example, by reducing manual order entry or helping employees access the right information faster.

At the same time, consider the foundation you are building on. A strong, integrated foundation makes it easier to take advantage of new AI capabilities as they mature – without first creating a fragmented landscape of disconnected tools and legacy systems that later need to be integrated, updated, or replaced.

Because the real opportunity is not more AI. It is AI that makes your logistics operations measurably smarter – without sacrificing control.