AI Agents helping Supply Chain Superheroes
Supply chain operations have long been at the forefront of automation, from barcodes and RFID to RPA and predictive analytics. Many supply chain leaders have already integrated robotic process automation into their workforce. But today, the complexity and dynamism of global supply chains demand more than static workflows or siloed bots.
According to EY, we can expect to see more organizations implementing agentic AI technology in their supply chains over the next 12 to 18 months. Agentic AI is the next wave of automation technology that is improving speed, efficiency and decision-making in the world of supply chain management. Let’s take a look at some potential use cases for Agentic AI for supply chain leaders.
Information Management and Decision-making
A foundational aspect of supply chain is the sheer volume of information being shared between systems and stakeholders at any given time. From materials suppliers to shipping facilities and distribution centers, endless information is being shared, and supply chain leaders constantly need to make decisions based on this information. When agents are involved in the end-to-end workflow, they can analyze the available information and make decisions to keep the process moving on schedule.
An aspect of supply chain where agents can help make decisions is inventory management. Leaders need to stay on top of which inventory should go where, which inventory needs to be purchased, and when inventory substitutions can take place. An agent can stay on top of this information and make and execute these intelligent decisions. It can also help make shipping decisions. The agent can review the type of shipment you need to make, analyze shipping rates or get quotes from shipping carriers, and then decide who to assign the shipment to. It can also handle delays and late shipments. Instead of having team members manually chase down late shipments, an agent can identify delays, reroute as needed, and alert customer service with a new delivery estimate.
Logistics and Compliance
Logistics and trade compliance are critical steps in the supply chain process, and when human resources are stretched thin, an agent can step in to unburden the human team and give them their time back.
An agent can read a Harmonized Trade Schedule (HTS) tariff code and make decisions regarding import and export documentation and classification. In cases where the HTS code is not known, the agent can search the system and make decisions based on the product and history to determine the proper HTS code needed to complete the import or export procedure.
Agents also operate within real-time policy and compliance guardrails. For example, they can deprioritize shipments from vendors flagged for ESG violations or automatically route tasks through compliant carriers based on up-to-date regulatory requirements. These embedded constraints ensure that execution remains aligned with enterprise values and evolving legal obligations.
Predictive Abilities
Today’s supply chain landscape is constantly changing and evolving to keep up with changes in the market. By deploying an agent to study real-time market data from multiple sources, it can integrate this data into forecasting models. By including more than just historical data in these forecasts, the agent can make more accurate predictions that reflect the current state of the market. An agent also reviews the production throughput, supplier performance, and logistics performance in making effective predictions for the supply side of operations.
Future Thoughts
As more agentic AI programs are deployed, supply chain executives must keep in mind that AI agents may not fully replace their existing resources. This technology must be integrated into existing workspaces to work alongside and augment human workers to maximize productivity, and worker satisfaction.