“Secure it cheap now, rather than buying it later.” For years, this principle underpinned freight procurement strategies. However, that logic is becoming increasingly outdated. A combination of rising trade barriers, geopolitical instability, energy price shocks, and volatile demand cycles has fundamentally reshaped the operating environment for global supply chains. Predictability, once the foundation of procurement planning, has become the exception rather than the rule.

In this new reality, traditional procurement models are struggling to keep pace. Conventional tenders rely heavily on historical data and the assumption of relatively stable conditions. Yet freight markets now shift in much shorter cycles, with routes, capacities, and costs constantly in flux. As a result, the gap between planning and execution is widening, creating inefficiencies that are becoming harder for businesses to absorb.

Ghost Lanes or Uncertain Capacities?

One of the clearest examples of this mismatch is the persistence of so-called “ghost lanes.” These occur when pre-secured Full Truckload (FTL) capacity goes unused. On average, up to 70% of contracted capacity is not fully utilised. While such agreements are designed to provide cost certainty and security of supply, they can ultimately have the opposite effect. Unused capacity still carries a cost, and when it is not called upon, it creates inefficiencies for both shippers and carriers.

For carriers, blocked capacity limits their ability to optimise routes and maximise utilisation. Over time, these inefficiencies are priced back into future contracts, driving up costs for shippers. What was intended as a safeguard against volatility instead becomes a contributor to it.

At the other end of the spectrum lies the spot market. Short-term procurement offers flexibility, but it introduces its own set of challenges. Operational complexity increases significantly, with tenders often managed manually and under tight time constraints. Price transparency can be limited, making it difficult to benchmark effectively, while fluctuating capacity availability reduces predictability. For many organisations, relying heavily on the spot market is simply not sustainable at scale.

How AI is reversing the tender process

This tension between long-term rigidity and short-term unpredictability is forcing procurement teams to rethink their approach. Increasingly, the focus is shifting toward solutions that can combine flexibility with efficiency, without adding further complexity. This is where AI-supported autonomous procurement is beginning to play a transformative role.

Rather than treating procurement as a periodic, event-driven activity, autonomous procurement enables a continuous, dynamic process. It allows organisations to respond in real time to changing market conditions, rather than relying on static assumptions set months in advance.

At the heart of this approach is a fundamental shift in how offers are generated. Traditionally, carriers calculate and submit bids in response to tenders. In an AI-driven model, this process is reversed. Shippers use algorithms to generate market-based offers themselves, drawing on a combination of historical data, real-time freight and spot rates, predefined pricing parameters, and logistical and sustainability considerations.

Crucially, these systems can also incorporate behavioural insights, such as the booking patterns and preferences of individual carriers. This enables more targeted and relevant offers, increasing the likelihood of successful matches.

Once generated, offers are published in real time on a digital platform. If a transport order is not immediately accepted, the system automatically initiates further tendering rounds, adjusting conditions and selecting alternative carriers as needed. This process runs autonomously, within defined guardrails, and is scalable across large networks.

Measurable efficiency and cost saving

The impact of this approach is already measurable. Match rates for FTL transport orders can reach up to 90%, significantly improving utilisation across the network. Matching times are reduced to an average of around 70 minutes, accelerating decision-making and execution. From a cost perspective, shippers are achieving spot rates that are typically 8% to 12% lower than traditional methods, while continuing to work with their existing carrier base.

Operationally, the benefits are equally compelling. Dispatch teams report productivity gains of around 20% per year, as manual workload is reduced and processes become more streamlined. Importantly, this also lowers the barrier to entry for less experienced team members, enabling them to manage spot procurement more effectively.

For carriers, the advantages are clear. The need for time-consuming bid calculations is removed, replaced by a simple acceptance process. This not only improves efficiency but also supports better planning and helps reduce empty runs, an ongoing challenge across the industry.

Conclusion 

Ultimately, the future of freight procurement will not be defined by ever more detailed long-term tenders. Instead, it will be shaped by the ability to remain flexible and responsive in the face of constant change. Organisations that can continuously adapt their decisions, without increasing complexity or cost, will be best positioned to navigate market volatility.

AI-powered autonomous procurement offers a pathway to achieve this. By combining real-time data, intelligent automation, and platform-based collaboration, it enables a more agile and efficient approach to managing freight capacity.

However, the effectiveness of such systems depends on one critical factor: data. The more structured and comprehensive the available data on freight flows, routes, and carrier performance, the more accurate and impactful the outcomes. This is why platform-based Transport Management Systems (TMS), particularly those connected to broad networks and reliable market data, are becoming essential infrastructure for modern procurement.

In a world where volatility is the norm, flexibility is no longer optional, it is a competitive advantage.