AI is driving productivity and profitability for business leaders across every industry and vertical. This is true especially for supply chain and transportation operations.
In many ways, the transportation industry has already reaped the obvious benefits of AI and automation. Transportation management systems (TMS) have already developed the capabilities you would expect AI to provide, like automated load planning, load optimization and consolidation and route management. There isn't much left for agentic AI to do in the operational transportation space that a traditional TMS doesn't already solve for.
However, AI does bring benefits to transportation that may not be immediately apparent.
Transportation analytics and insight
While AI may already have reached its existing potential in transportation planning and execution, it has much more untapped potential in transportation analytics and insight.
The hallmark of a mature transportation network is data availability and nuanced reporting dashboards. Anyone who's ever been tasked with setting up a transportation dashboard knows that the task ranges from daunting to incredibly difficult. AI can help streamline the process of gleaning meaningful insights from your network, reducing the number of hours spent identifying relevant data and configuring data views for your company.
As always, there is a catch. Although AI can provide valuable insight into your transportation network metrics, as with a traditional transportation dashboard, that insight will only be as good as the data your company is capturing today. In a transportation network that isn't capturing necessary data elements like carrier performance and shipping date flexibility, AI functionality will fall short of transforming a transportation network from undeveloped to mature.
This is where a TMS comes in.
TMS as the bridge to AI-enabled transportation insights
Luckily for today’s transportation leaders, the easiest solution for capturing the required data elements that will ensure you get the most value out of AI in a transportation network already exists. It’s a TMS.
TMSs provide a central source of truth for transportation data and should serve as the system of record for all shipments. This means that rather than piecing together a dashboard from various sources, dashboards that rely on TMS data are typically more accurate, consistent and free from exceptions.
Additionally, TMSs capture more data than you might expect, such as historical carrier performance, routing compliance and delay information. Seasoned transportation data specialists can leverage this data to construct transportation management scenarios that can help their company realize tangible savings or efficiencies. When paired with an AI-powered reporting tool, that process can be automated, providing transportation leaders with a natural-language interface into their entire transportation network.
Not all TMSs are created equal. Selecting the right one for your business can help standardize your transportation network’s data elements, provide a source of truth for shipping information and cost and be a springboard for AI-developed dashboarding and insight.
When selecting the TMS that will be the foundation for your AI-enabled transportation insights, consider key elements like available data fields, data retention policies, scalability, planning and optimization tools, integration capabilities and ready to use reporting and analytic dashboards. To make sure you get it right, you might consider bringing in a third-party consultant that has made these decisions before and can guide you to the right system.
Conclusion
As for any area of the supply chain, AI isn’t a magic bullet for transportation management. The value you get out of AI-powered analytics and insights is highly dependent upon the quality of the data that already exists within an organization. Having a TMS that can lay the groundwork with a single source of data truth is absolutely essential for getting the most value out of AI in your transportation network.
