AI use-case directory · Logistics & Warehousing

Shipment ETA prediction: real AI examples and a starter prompt

AI predicts when ocean, air or truck shipments will really arrive using vessel positions, port congestion and history, so planners can act on delays early.

Best for: Logistics leads, Planners

Real-world examples

Ligentia

Saw 39% higher ETA accuracy, and 70% higher accuracy within 24 hours, compared with carrier ETAs.

Source: Windward case study

Hapag-Lloyd

Uses HERE location data on AWS to deliver near real-time predictive ETAs for container movements across transport modes.

Source: AWS case study

Tools

Free or low-cost options first, then enterprise platforms.

Carrier tracking + General-purpose AI assistant (ChatGPT, Claude, Gemini, Copilot; free tiers) to summarize exceptions
project44
FourKites
Windward

Starter prompt

Replace the [BRACKETS]. Remove names and confidential numbers first.

Here is an anonymized list of open shipments (origin, destination, mode, carrier ETA, last event). Flag the ones most likely to be late based on the last event and typical dwell times, and draft a short note to the affected planners.

Related Brief coverage

#freight

More logistics & warehousing use cases

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