Samsung SDS is leveraging machine learning and generative AI to detect supply chain risks in real time and quickly develop response strategies. In April, the company was able to instantly detect the escalating conflict between Israel and Iran and notify customers about the impact on air freight bound for Israel—thanks to this real-time risk detection capability.

At the Cello Square Conference 2024 held on April 20 under the theme ¡°Digital Logistics Strategies for Responding to Global Risks¡±, Samsung SDS presented AI-powered digital logistics strategies for managing global supply chain risks.

Reducing Risk Response Time from One Day to Two Hours

Since the COVID-19 pandemic, the global supply chain has faced several disruptions, including:

*Geopolitical risks such as the Russia-Ukraine war and the Red Sea logistics crisis *Reorganization of global supply chains due to growing protectionism in the U.S. and Europe *Climate-related challenges, including stricter carbon emission regulations

Koo-il Oh, Head of the Logistics Business Division at Samsung SDS, emphasized the need for digital transformation in logistics to effectively respond to these rapidly changing global conditions. He also introduced strategies and case studies aimed at minimizing the impact of such risks.

Samsung SDS automatically extracts logistics risks using machine learning from over 60,000 global news articles collected daily. These risks are then evaluated using generative AI, which classifies them into three levels of severity. The company has trained its generative AI model using around 20,000 past global logistics risk cases.

Once the affected shipment volume is automatically calculated, logistics experts at Samsung SDS analyze the data and apply their expertise to quickly develop response strategies. This process, which previously took a full day, has now been reduced to just two hours—greatly improving the speed of risk response.

For instance, when the Israel-Iran conflict was detected in April, Samsung SDS immediately proposed an alternative shipping plan: rerouting cargo to nearby ports in Oman and the UAE, and using neighboring countries for onward transport. This enabled them to complete the delivery on schedule.

Additionally, Samsung SDS is implementing hyper-automation in customer service and logistics operations using generative AI. Previously, customers had to navigate various menus on the digital logistics platform, Cello Square, to access information. Now, they can simply interact with a generative AI chatbot to obtain estimates, calculate the number of containers needed, and more—easily and efficiently.

Even traditionally manual and repetitive logistics operations are being automated with AI. For example, rather than manually retrieving shipment and billing data from the system for each customer, generative AI now enables employees to extract this information through a simple conversation.

Cello Square also provides real-time data on cargo movement, shipping delays, port congestion, and container status. By analyzing historical data, the system offers predictive ETA (Estimated Time of Arrival) by calculating expected ship travel time and port dwell time. It can even forecast abnormal events like port detention or demurrage fees and predict future costs, offering greater financial visibility.

Moreover, Cello Square supports ESG (Environmental, Social, Governance) management by displaying carbon emissions and carbon intensity by transport mode (air, sea, land, rail), and provides various solutions to help customers reduce emissions.

Managing Logistics Risks in Vietnam via Cello Square

Samsung SDS also shared a specific case study on how it responded to logistics risks in Vietnam.

As more companies shift operations to Southeast Asia—particularly Vietnam—due to rising trade tensions with North America, logistics risks have emerged from the underdeveloped infrastructure and limited local knowledge. These include customs clearance issues causing production delays, inventory mismanagement leading to major penalties, missed sales opportunities due to blank sailings or the Red Sea crisis, and loss of trust due to stockouts and partial orders.

Dong-gyun Kim, Head of the Southeast Asia Region at Samsung SDS, explained that these problems are being addressed through a combination of proprietary systems and localized logistics experts.

For example, customs clearance risks for equipment imports—often caused by regulatory misunderstandings or discrepancies in documentation—are mitigated by using AI to track regulatory changes and by managing imports as turnkey projects to prevent workflow disruptions.

To handle maritime shipping delays caused by blank sailings or geopolitical issues, Samsung SDS recommends optimal shipping lines and accurate schedules based on big data. By analyzing inventory in transit by arrival date, they can calculate available stock by day and align this with production and sales plans—enabling accurate delivery schedules for customers.

In response to inventory issues like stockouts, aging, and quality/cost increases caused by manual warehouse operations, Samsung SDS is overhauling its logistics infrastructure, processes, and systems. Using PDAs and the Cello system, inventory data is aligned with physical goods, preventing errors like stockouts or partial orders and enabling FIFO (First In, First Out) management to control product aging.

Koo-il Oh concluded, ¡°In the wake of continuous global risks since COVID-19, demand for logistics digital transformation has grown significantly. Samsung SDS will continue to provide uninterrupted and sustainable logistics services by utilizing digital technology and AI to adapt to major changes in global supply chains.¡±