Agentic artificial intelligence is expected to help logistics companies cope with supply chain crises and reduce the burden of tariffs, shipping costs and environmental expenses, industry forecasts suggest.
Samsung SDS held the "Cello Square Conference 2026" at its logistics campus in Pangyo, Seongnam, Gyeonggi Province, on Monday. The event brought together 120 shipper companies in the manufacturing and distribution sectors to share strategies for responding to global supply chain crises and key logistics industry trends. In line with this year's theme, "The Era of Agentic AI Supply Chains," Samsung SDS used generative AI to analyze a wide range of data and identified 10 major industry trends.
Based on those 10 trends, Samsung SDS presented three core insights: △an automated control tower capable of decision-making, △the rise of digital twins that support complex decision-making, and △the expansion of total-cost-based decision-making that accounts for both direct and indirect logistics costs. Oh Gu-il, executive vice president of Samsung SDS's logistics business division, delivered the keynote address and explained the three insights.
The automated decision-making control tower is an operating system that integrates data in real time across the entire supply chain — from production to transportation to inventory — to secure visibility. AI-powered analytics can detect and respond to anomalies such as demand fluctuations or shipping delays in advance. By leveraging the automated control tower, companies can move beyond simple logistics monitoring toward autonomous operations that incorporate predictive and preemptive decision-making.
The rise of digital twins is linked to simulation for optimized workflow design within organizations. As global supply chains grow increasingly complex, collaboration among warehouse workers, automated equipment and AI is expanding, making optimal role allocation more important. This is where simulation using digital twins becomes necessary. Oh projected that the use of digital twin simulations will also expand for reviewing alternatives in response to variables that arise in actual logistics operating environments.
Total-cost-based decision-making refers to decisions that reflect not only traditional costs such as shipping fees and tariffs but also carbon emissions, supply chain risks and the opportunity cost of cargo in transit. Samsung SDS explained that total-cost-based decision-making can drive cost savings as well as the establishment of supply chain strategies that incorporate sustainability.
"Samsung SDS plans to combine rich field data with advanced AI technology to help customers make rapid decisions and build resilient supply chains," Oh said.