Supply chain and logistics management are fraught with complexity and challenges. From managing intricate carrier relationships to navigating global import/export regulations, the industry is riddled with challenges. These hurdles, combined with the dynamic and often opaque requirements across different regions, force businesses to adopt contingency plans upon contingency plans.
Every industry looks to make the best decisions with the constraints and mandates they have and seize any opportunity to improve first to last mile delivery. While topics like data ontologies and route optimization aim to inform decisions using the structured data common in logistics, there is increasing attention on Generative AI (GenAI).
Let’s dive into three key areas where customers are seeing opportunities to use GenAI for logistics challenges:
1. Optimizing Loading Plans With Retrieval-Augmented Generation (RAG)
Are your loading plans optimized? Many aren’t.
According to MIT Sloan Management Review, "Trucks in the U.S. are about 30% empty on average, which wastes time, fuel, and leads to unnecessary carbon emissions." Optimizing capacity is a key objective for all organizations but, in order to do so, you need more than just solvers and algorithms. You need to prescriptively provide coordinators, planners and dispatchers with easy to understand advice.
It’s all about supporting the decision making of decision makers. GenAI provides a great way to do just this by making optimization and AI understandable and explainable. RAG models simplify the complex and create an accessible way to surface insights and recommendations so loading plans and routes can be optimized. This translates into action taken and value generated.
2. Surfacing Risk in Transportation Corridors
Do you know which transportation corridors pose the greatest risk? And do you have a contingency plan in place?
Hurricane Helene recently illustrated that, despite forewarning, supply chains that are inherently complex and interdependent remain brittle and prone to disruption. Those disruptions vary by region, product line, supplier, distribution center, and beyond. Geopolitical variables as well as micro and macroeconomic stressors all contribute to an environment of ever-changing uncertainty. To help manage this complexity and identify transportation and delivery risks, some manufacturers are using GenAI to scour the internet, annual reports, and news articles.
One large logistics company is using the technology to quickly flag risky routes and transportation corridors so the supply chain team can create more robust contingency plans. The planning team also uses this risk assessment information to better manage customer service and expectations and quickly communicate disruptions to the end customer.
3. Improving Data Quality in Warehousing and Logistics
Is your data house in order? Probably not – especially in logistics and warehousing.
Many logistics operations deal with messy, unstructured data sources, like warehouse and carrier logs, which are often underutilized. Traditional systems struggle to leverage this data effectively due to its free-form nature. However, GenAI can turn disorganized text into structured, usable information.
For example, a pharmaceutical company is using GenAI to extract specific failure information from maintenance logs. This allows the company to determine which parts and tools are needed for equipment repairs, improving first-time fix rates and reducing repair times for warehouse machinery. The benefits are clear: greater operational efficiency and reduced downtime, all thanks to better data quality.
Drive Efficiency With GenAI in Logistics and Supply Chain
As supply chain operations and logistics challenges continue to evolve, GenAI is emerging as a powerful tool to optimize operations, surface risks, and improve data quality. Whether it’s reducing empty truck capacity, identifying risky transportation corridors, or transforming unstructured data into actionable insights, GenAI provides solutions that drive efficiency, resilience, and value across the supply chain. The future of logistics is here, and it's powered by AI.