AI for transport optimisation applies artificial intelligence to analyse and improve logistics operations in real time. Unlike manual planning or static TMS algorithms, AI transportation management simultaneously considers dozens of variables: vehicle availability, driver working hours, current road conditions, exchange rates and order history.
Transport companies using AI for route optimisation report an average 8 to 15% reduction in fuel costs and 12 to 18% increase in orders handled without expanding their fleet.
Where does AI generate the biggest savings?
- Empty runs
- Reduction of 15 to 25% through intelligent backload matching and route consolidation
- Fuel costs
- Reduction of 8 to 12% through route optimisation accounting for current road conditions
- Outsourcing costs
- Reduction of 10 to 15% through better carrier selection and automated rate negotiation
- Planning time
- Reduction of 60 to 70%: dispatchers spend 3× less time on manual route planning
First optimisation effects are visible in the first month, mainly in empty run elimination and better carrier selection. Full AI optimisation potential emerges after 2 to 3 months when the system has enough historical data to learn from.
No. Bobi optimises both own-fleet transport and subcontracted orders. For pure freight forwarding companies (without own fleet) it focuses on carrier selection optimisation, quoting and load consolidation.
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Book optimisation analysis: Bobi AI