How AI is being used in transportation management systems today

Artificial Intelligence has quickly become one of the most talked about technologies in supply chain and logistics. From industry conferences to vendor announcements, AI is often positioned as a transformative force. But behind the headlines, a more practical question remains: is AI truly being used in transportation management systems today and if so, where is it actually delivering value? The answer is more nuanced than many expect. While interest in AI is high, much of its application in logistics today remains limited to analytics, visibility, or isolated use cases. In many cases, AI is discussed more than it is operationalized. The organizations seeing real results are not those applying AI broadly, but those applying it selectively at key decision points where data, repetition and measurable outcomes intersect. Within Transportation Management Systems (TMS), this means embedding AI into workflows that directly impact cost, execution and financial control. Where nVision Global is delivering real value with AI At nVision Global, the approach to Artificial Intelligence within transportation management has been deliberate and focused. Rather than applying AI broadly, the emphasis has been on identifying specific decision points within the transportation lifecycle where data, repetition and measurable outcomes create the greatest opportunity for improvement. Transportation operations generate vast amounts of data, from shipment characteristics and lane history to transportation provider performance and pricing trends. Within IMPACT TMS, nVision has found that AI delivers the most value when applied to decisions that occur frequently and benefit from continuous learning. This has led to the targeted implementation of AI across three core areas: procurement optimization, shipment approval workflows and execution automation. Smarter procurement through AI-driven spot auctions One of the first areas nVision focused on was the spot auction process, an area that has traditionally relied on manual decision-making or static routing guides. Within IMPACT TMS, AI is used to dynamically determine which transportation providers should be included in each spot auction. Rather than applying fixed rules, the system evaluates each shipment individually, analyzing attributes such as lane, commodity, equipment requirements and timing. This is combined with continuously evolving data on provider pricing behavior, service reliability and historical performance. The result is a tailored list of transportation providers for every auction, sometimes expanding participation, other times narrowing it, based on what is most likely to drive the best outcome. By embedding this intelligence directly into the procurement process, nVision has enabled more consistent, data-driven decision-making that improves both efficiency and results. Intelligent shipment approval workflows nVision has also identified shipment approval as a critical control point where AI can deliver meaningful value. In many environments, approval workflows are static and fail to reflect the unique characteristics of each shipment. Within IMPACT TMS, AI introduces a more dynamic and contextual approach. By analyzing shipment details, such as origin, destination, cost and who initiated the shipment, the system determines who should be involved in the approval process, whether multiple layers of approval are required, and how the workflow should be managed, including reminders and escalations. Beyond workflow automation, the approval process also provides decision support. Approvers are given visibility into whether the selected transportation provider represents the lowest-cost or most appropriate option, enabling them to challenge decisions before the shipment moves, rather than after costs are incurred. This approach allows nVision’s clients to shift financial control earlier in the process, where it has the greatest impact. Automating execution with AI-driven tendering With procurement and approval processes enhanced through AI, nVision extended this approach into execution through automated tendering. Within IMPACT TMS, once a shipment has been rates, auctioned and approved, the system automatically tenders the load to the selected transportation provider, delivers all required documentation and monitors acceptance. If the provider declines or does not respond, the system continues through a prioritized sequence until the shipment is secured. This creates a continuous, intelligent workflow that removes the need for manual follow-up while improving speed, consistency and reliability. By applying AI at this stage, nVision has reduced administrative burden while ensuring that execution aligns with the decisions made earlier in the process. A more integrated approach to AI in TMS nVision Global’s experience has shown that the value of AI is not just in isolated features, but in how it is applied across connected workflows. By embedding AI across spot auction execution, shipment approval and auto tendering, IMPACT TMS creates a unified, end-to-end decision framework, linking procurement, governance and execution in a way that allows organizations to influence outcomes before costs are incurred. This level of integration reflects a more practical application of AI in transportation management, one that moves beyond theory and into measurable operational impact. The path forward At nVision Global, AI is viewed as a tool to enhance, not replace, people and their transportation expertise. Its value comes from being applied thoughtfully, in areas where it can improve consistency, reduce manual effort and support better decision-making. As adoption continues to grow across the industry, the distinction will not be in who is talking about AI, but in who is applying it in ways that deliver real, measurable results.