Rob Cook

Your TMS and ERP aren’t enough. Despite billions spent on supply chain tech, most teams still run on PDFs, spreadsheets, and email threads—creating manual chaos that slows everything down. This eye-opening white paper reveals how top supply chain teams are using an invisible layer of AI to streamline operations—no dashboards, no extra headcount, no noise.   Download now to learn how to eliminate manual bottlenecks and give logistics teams their time—and sanity—back. Uncover the hidden gems – Manual workflows waste hours and create delays. Learn how to fix it fast. See real results – Cut shipment intake from 30 minutes to 10 seconds, without new tools or extra headcount. Discover smart automation – Learn how to turn messy emails and PDFs into structured data that flows seamlessly into your systems.   Ditch manual chaos and see how an ambient back office that never sleeps can save your team thousands of hours, eliminate costly errors, and unlock the true potential of your supply chain.   Download the white paper here to learn more  

Special Guest Blog Post written by Dr. Johannes Hangl with e2open   AI is no longer an experiment in global trade compliance. It’s already being applied in product classification, document-to-declaration workflows, risk targeting, and sanctions screening. At the same time, regulators and customs authorities are adopting AI themselves. This is raising expectations for data quality, transparency, and governance across the entire trade ecosystem. With the EU AI Act set to apply from August 2026, companies that have not yet implemented human-in-the-loop controls, drift monitoring, and defensible audit trails are running out of time to close the gap.   Where AI is already adding real value today: HS and ECN classification   Product classification has become one of the most practical AI use cases. Modern tools can now suggest harmonized system (HS/ HTS) and export control (ECCN) codes, explain the rationale, and attach confidence scores and audit metadata to each decision. This direction mirrors what customs authorities are doing. Administrations such as German Customs have discussed using machine learning to improve targeting and risk detection. It appears both sides of the border are moving toward data-driven decision support. AI does not remove accountability. It changes how accountability is exercised.   Practical…