Freight procurement is facing shorter market cycles as geopolitical uncertainty, trade restrictions, energy costs and fluctuating demand disrupt established planning models.
Long-term contracts can leave shippers paying for capacity they do not use. Up to 70% of contracted FTL capacity may remain idle, creating “ghost lanes” that also prevent carriers from using vehicles efficiently. Spot purchasing offers flexibility, but manual tendering, limited price visibility and uncertain availability make it difficult to scale.
AI-supported autonomous procurement is emerging as an alternative. Algorithms create offers using historical transport data, current freight and spot rates, pricing rules, logistics requirements and sustainability criteria. They can also consider individual carrier preferences and booking behaviour.
Once published on a digital platform, an offer can trigger further tender rounds if it is not accepted. Conditions may be adjusted and alternative carriers selected automatically within predefined controls.
Reported performance includes FTL match rates of up to 90%, average matching times of about 70 minutes and spot rates 8–12% below traditional methods. Dispatch productivity has improved by around 20% annually in the cited results, while carriers benefit from simpler acceptance and potentially fewer empty runs.
The approach depends on structured data covering routes, freight flows and carrier performance. Connected TMS platforms and digital transport networks are therefore becoming increasingly important to industrial companies seeking resilience without adding administrative cost. Trimble is one provider operating in this market.
A multilingual professional experienced in Europe, Canada, and China, Herbert has developed invaluable networks in the automotive and energy industries. He has led high-profile projects involving ENBW, Mercedes-Benz Group, Siemens Group, and the Fraunhofer Institute.