AI · July 30, 2026 · 8 min read
Applied AI in logistics: where it pays, where it doesn't
AI in logistics earns its keep in three places: predicting, reading, and triaging. Everything else is usually a dashboard with better marketing.
Prediction: ETAs and dwell
Historical stop data plus live telematics beats carrier-provided ETAs quickly. Accuracy targets should be stated in minutes, per lane, and tracked weekly.
Reading: documents
BOLs, PODs, customs paperwork, and invoices are high-volume, semi-structured, and expensive to key. Extraction with human review on low-confidence fields is the reliable pattern.
Triage: exceptions
Ranking exceptions by financial and SLA impact lets a small ops team work the queue that matters instead of the queue that scrolls.
Data prerequisites
Consistent event timestamps, stable location identifiers, and labeled outcomes. Without those, no model will outperform a good rule.
What to skip early
Autonomous decisioning without a human in the loop, and forecasting on fewer than a few seasons of clean history.
Building something like this?
Wve Labs designs and builds custom logistics apps, portals, and platforms. Tell us how your freight moves and we'll scope the build.