AI’s applicability is often overstated, but it delivers exceptional value for managing and keeping carriers’ accessorial charges in check.
In software circles, AI is the innovation of our time—but as many are realizing, what gets labeled “AI” is often more accurately described as powerful database and analytics technology. And the distinctions don’t end there.
Large Language Models are great at finding patterns and discerning information within massive data sets, but they are stateless and do not learn in the traditional sense – at least not yet. Agentic AI, with capabilities that come closer to intelligence as we typically define it. But here again, there are significant limitations. Even retrieval-augmented generation (RAG) is not really memory as we associate it with the human brain; instead, it reflects the use of powerful database capabilities.
I say this not to diminish AI—at Reveel, we’ve been proponents of AI and have used it to deliver new capabilities through our platform for years. But context matters. In a time when everyone touts AI’s value, shippers need to know where the hyperbole ends and the real benefits begin.
Why AI Is Ideal For Parcel Shipping
Here’s the good news: some of the things AI does best today are directly applicable to parcel shipping.
The data sets we use most often—carrier invoice data and internally-generated manifest order data—are both finite and include many thousands of rows of entries. This makes them precisely the kind of diverse but organized data that lends itself to the effective training of AI models.
This matters because each shipment is influenced by numerous and continuously changing variables. Shipping data is exactly the kind of information that existing AI models can most effectively analyze. And that capability couldn’t be more timely.
The Accessorial Charge Problem
Nothing puts this in context better than carrier’s favorite strategy to increase their profits today: accessorial charge. While General Rate Increases (GRIs) were once fairly predictable, accessorial charges now change with increasing frequency and little warning. Common examples include:
- Extra fees for oversize or irregularly shaped packages
- Delivery area surcharges expanded to include zip codes in major metro areas that were never previously classified as “remote”
- Peak season surcharges that extend well beyond traditional holiday windows
- Address correction fees triggered by minor data discrepancies
These charges add up quickly—and without sophisticated pattern recognition, they’re nearly impossible to track manually across thousands of shipments.
How AI Keeps Accessorial Costs in Check
AI’s ability to analyze massive data sets and identify anomalies makes it uniquely suited for accessorial management. Rather than discovering costly surcharge patterns months after the fact, AI-powered tools can flag issues in real time, giving shippers the opportunity to adjust before costs spiral.
This is exactly why we developed our Parcel Spend Management 2.0 technology—to help shippers stay ahead of carrier pricing strategies rather than constantly reacting to them.
Want to dive deeper? Our recent webinar, “How to Predict & Analyze 2026 Accessorials,” covers these topics in detail. It’s a must-watch for any shipper looking to make sense of today’s parcel shipping environment and learn how AI tools can help keep costs down.
