Monica Aurora Roesch Davila

Special guest post written by Chris Cunnane with InterSystems Supply chain orchestration is the coordinated management of end-to-end supply chain activities, across planning, sourcing, production, logistics, and delivery, using technology, data, and processes to ensure that every moving part works together seamlessly. It enables organizations to attain an agile and resilient supply chain model through the use of decision intelligence. This is achieved through the See > Understand > Optimize > Act framework, which gives organizations the confidence to plan and respond to disruptions with assurance in their supply chain stability. See: gather raw data and information from your environment or a situation. Understand: analyze the information you’ve seen to build a comprehensive understanding of the context, your knowledge, and potential complexities. Optimize: develop the best possible solution or course of action to address the situation. Act: implement your chosen solution, putting your knowledge into practice. From a practical standpoint, this framework powers your supply chain application ecosystem with end-to-end visibility, insights, and better decisions. It helps organizations reach their supply chain goals by enabling them to align processes, stakeholders, and technology toward desired outcomes. The end result is reduced costs, improved operating margins, and optimized sustainability decisions, among others.…

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…