AI in Logistics & Transport: Routing, Tracking & Dispatch
Route optimisation, customer tracking assistants, demand-driven dispatch, and fleet maintenance prediction — where AI cuts cost and delay in logistics.
Logistics is a margins game where the enemies are empty kilometres, idle vehicles, and "where is my package?" phone calls. AI attacks all three.
Proven Use Cases
1. Customer Tracking & Booking Assistants
The single biggest call-centre load in delivery businesses is status inquiries. An assistant that reads live tracking data answers "where is my order?" instantly on WhatsApp — and takes new bookings while it's at it.
2. Route Optimisation
Multi-stop route planning that accounts for traffic, delivery windows, and vehicle capacity. Even simple optimisation typically cuts fuel and time 10-20% versus manual planning.
3. Dispatch Automation
Matching jobs to the nearest suitable vehicle/rider automatically — the logic that powers ride-hailing, now accessible to any delivery fleet.
Emerging Use Cases
- Demand forecasting — positioning vehicles and stock where tomorrow's orders will be.
- Predictive maintenance — flagging vehicles before breakdowns from telemetry and service history.
- Document automation — reading waybills, customs forms, and PODs to kill manual data entry.
The Realistic First Step
A tracking and booking assistant connected to your operations data. It removes the largest share of inbound calls on day one and builds the data foundation for routing and dispatch optimisation later.
Part of our AI Use Cases by Industry series. Moving goods or people? Talk to us.