One AI agent could end logistics data chaos

For more than 40 years, the transportation and logistics industry has settled into an inefficient status quo, struggling to manage fragmented data across multiple systems. Many logistics professionals still rely on a “swivel-chair” workflow, moving between different platforms, databases and enterprise systems to find the information they need to keep freight moving.

For a transport coordinator, this can mean manually switching between a transport management system, tracking platforms, spreadsheets and other operational tools. Time that could be spent solving problems and improving customer service is instead lost navigating disconnected systems.

The industry has already started exploring a solution: an army of specialised AI tools that can handle some manual and repetitive tasks.

While it’s clear that AI will be a defining technology in transforming the way freight moves around the world, the current approach of creating separate AI tools for every individual task needs to be evaluated and refined. Our coordinators’ chairs haven’t actually stopped swivelling between screens yet – they are ready for a more efficient approach.

What businesses need is a single AI agent that can help them swiftly and reliably navigate this complex ecosystem, managed securely from a single pane of glass, reducing the swivel-chair workflow once and for all.

Supercharging AI

Despite the challenges of today’s AI landscape, it’s easy to see how and why the industry has arrived here.

In the internet’s early days, users were accustomed to finding information through curated web directories. It was similar to using a phone book or reference library, navigating through multiple categories to find what was needed.

That experience has evolved significantly, but businesses still face a similar challenge with AI agents today. Organisations are required to identify the right tool for each task, provide the appropriate prompts and coordinate the next steps between systems.

A single AI agent can provide a more unified experience, allowing users to give a natural-language instruction and enabling the system to identify the right data and tools across an enterprise ecosystem to complete the task.

Single, safe agent

The true power of AI in logistics does not come from a tool that can simply write emails, answer questions or translate text. It comes from the ability to support complex operational decisions across multiple platforms and data sources.

One supply chain task that could benefit from this approach is resolving a problematic shipment – a process that may currently require extracting account histories from a TMS, cross-referencing a spreadsheet for spot rates, checking market information online and then documenting a revised routing strategy within fleet management software.

Today, businesses can achieve parts of this using multiple AI tools. However, a more connected AI agent could complete this chain of actions more quickly, helping operators make decisions faster and reducing administrative effort.

However, this efficiency comes with important security requirements that must be robust.

Uncompromising security

An AI agent’s safety measures must match its operational access. For a unified agent to reach its full potential, it needs to be able to access and interact with live business data and internal systems.

In an environment like this, even a small lapse in security could create significant risk.

Today’s most common consumer-grade AI tools are not designed for the complex needs of logistics. Supply chain teams need solutions with comprehensive audit trails, user controls and strict cost management. The last thing businesses need is an AI tool operating without accountability.

Uncontrolled autonomy also creates risks. AI solutions that lack proper security oversight can attempt to complete tasks in unexpected ways, potentially creating new connections or bypassing controls.

In a live operational environment, this type of behaviour is unacceptable.

True enterprise safety means enforcing clear boundaries. A powerful agent must operate with visibility, user permissions, cost controls and strong data security.

Realising next-generation AI

The creation of a safe, unified AI structure is not just a promise of the technology hype cycle; it represents a potential next step for the global transportation and logistics industry.

Because supply chains operate at huge scale and with tight margins, operators should not settle for consumer-facing solutions that cannot meet the sector’s complex requirements.

By combining enterprise security with the ability to support day-to-day operations in a single AI agent, businesses can begin breaking down fragmented workflows and create a more connected future for the supply chain.

Jonah McIntire, chief product and technology officer at Trimble