After big data, blockchain, and the metaverse faded from headlines, AI has emerged as the latest technology trend. But is it merely another buzzword or a fundamental shift in container supply chain operations?
The evidence suggests genuine transformation. AI's value proposition aligns precisely with container logistics structure: fragmented stakeholders, unstructured documentation, multilingual communications and operational complexity. The technology transforms unstructured data into structured, actionable information — directly addressing the industry's most persistent inefficiencies.
Client demonstrations consistently generate "wow" moments as logistics professionals recognize AI's practical impact in numerous use cases, including intelligent vessel selection analyzing carrier allocations, freight costs, ETAs, ETDs, CO2 emissions, and direct versus transshipment routing to optimize booking decisions; automated documentation workflows submitting booking requests, verified gross mass declarations, and shipping instructions without manual intervention; smart document classification automatically identifying incoming email attachments and associating them with correct shipments; bill of lading verification comparing draft bills of lading against shipping instructions to catch discrepancies; and shipment creation from email extracting booking details from importer communications.
By extracting data from unstructured documents and integrating it with robust booking workflows, AI accelerates manual tasks while maintaining procedural compliance and ensuring optimal shipment routing.
However, projections indicate AI's global energy requirements will equal 70 nuclear power plants by 2030. We may face a choice between boiling your morning tea or making an AI query. This energy demand will drive AI-pricing sky high, forcing more rigorous ROI evaluation and strategic selection of use cases rather than blanket implementation across all operations.