CHECKINGIN
Vol. 46, No. 5
May 2026
THE MAGAZINE FOR DEMAND-DRIVEN ENTERPRISES www.inboundlogistics.com
AI and TMS Integration
STAFF
Keith G. Biondo publisher@inboundlogistics.com Felecia J. Stratton editor@inboundlogistics.com Katrina C. Arabe karabe@inboundlogistics.com
PUBLISHER
F or decades, the core transportation management system (TMS) served as the reliable engine of enterprise logistics. Today, an exciting age of enhancement is upon us and just in time, too. In an era de ned by volatile supply chains and unpredictable disruptions, static planning is legacy. But guess what? You need not completely replace legacy TMS infrastructure. Instead, augment it with an intelligent layer: the strategic integration of
EDITOR
SENIOR EDITOR
DIRECTOR OF STRATEGIC CONTENT
Amy Roach amy.roach@thomasnet.com
Ashley Prince ashley.prince@thomasnet.com
ASSOCIATE EDITOR
Keith Biondo, Publisher
Tom Gresham Karen M. Kroll Rich Osborne Gary Wollenhaupt
arti cial intelligence. Bridging the gap between legacy systems and modern TMS/AI is not an impossible technical hurdle; it is a doable modernization strategy. Let’s look at the process. First, the existing data is checked to ensure high data quality and compatibility across disparate systems. GIGO (garbage in/garbage out) on AI is not fun. Next, the AI is laid over the existing enterprise resource planning (ERP) system via APIs, which allows the legacy TMS to remain in charge while AI feeds it dynamic instructions. Then comes testing, testing, and more testing. A human is kept in the loop because we all have been told AI can make mistakes. Integrating AI and TMS is being done; you’ll nd some examples in our TMS article on page 38. Today’s AI-enhanced platforms process hundreds of variables concurrently—from real-time traf c conditions and severe weather to driver compliance, emissions thresholds, and dynamic cost uctuations. Instead of relying on pre-set, pre-planned routes, operations can now achieve continuous re-optimization as real-world disruptions wreak havoc on your product ow. One case history we covered shows a global carrier integrating AI routing engines and successfully reducing driving distances by more than 100 million miles annually. Besides the obvious bene ts, it also resulted in saving millions of gallons of fuel and cutting corporate carbon footprints. Similarly, a leading third-party logistics provider deployed powered AI to ingest, validate, and process complex transport data, allowing them to handle 30% more volume with the same workforce size while drastically improving response speeds to their customers’ inquiries. Those bene ts are passed to you. Of course, if you are large enough to be running your own TMS, you too can get similar AI overlay results. Either way, the ef ciency of a TMS/AI is real. There’s nothing arti cial about that.
CONTRIBUTING EDITORS
Jeof Vita jvita@inboundlogistics.com
CREATIVE DIRECTOR
DESIGNER Arlene So
DIGITAL DESIGN MANAGER PUBLICATION MANAGER
Amy Palmisano apalmisano@inboundlogistics.com
Sonia Casiano sonia@inboundlogistics.com
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4 Inbound Logistics • May 2026
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