Information is king for industrial manufacturers. From production process control to locating goods during manufacture and delivery, real-time visibility into the how, when and where of your raw materials, components and finished products can help you make the right decisions when they matter.
In today’s industry, information itself is not enough. The right tools are essential to make the most effective use of critical data points and other inputs because your operations produce more data than a human may know what to do with. It’s why artificial intelligence (AI) systems have begun to make a major impact for supply chains everywhere. Specifically, agentic AI—which maintains a higher degree of autonomy and can generate actions and decisions without human intervention—represents the next step in an ongoing information revolution. Indeed, early adopters of such technology in supply chain management are already realizing improved inventory levels, enhanced customer service, reduced logistics costs and more.
By leveraging advanced machine learning and natural language processing, agentic AI builds on previous experiences and merges new data with historical information, allowing it to make measurable, real-world differences in manufacturing supply chain management. Traditional AI waits for human prompts; agentic AI analyzes, learns and makes decisions on its own. It’s a supply chain game-changer that no one can afford to ignore.
Empowering Deeper Insights
Agentic AI enables manufacturers to realize some significant benefits, including:
- Automating workflows
- Tracking shipments in real-time
- Optimizing loads and routes
- Enhancing customer service
Agentic AI is also capable of assessing operations and suggesting productivity improvements to your workflows. For example: Do you know how many specific touch points there are in your manufacturing process? Sourcing, procurement, packaging, labeling, the list goes on, and agentic AI can analyze them to see whether it's possible to reduce the number with no adverse effects on product quality.
Further, in pursuit of supply chain resilience, agentic AI can analyze massive volumes of data while easily delivering the required information to supply chain managers. Unlike traditional AI tools which require a human to identify the data and guide analysis through a series of prompts, agentic AI handles the task itself based on analyses it has already performed.
As a result, people can focus on handling more complex and often nuanced tasks involving real-world interactions. Any operation runs more smoothly when its team members can spend more time doing what they do best.
Total Integration
Agentic AI's ability to learn from previous tasks is what separates it from traditional AI tools. A forecast might identify a potential stockout in the future. Agentic AI, having learned from experience, can tell whether that demand indicates a trend that may necessitate a shift in production—or if it’s just an outlier that does not require significant action.
This sort of information can be gleaned from market trends, competitor information, historical statistics and more, enabling agentic AI to notice things like rising costs before proactively developing a solution. From this information, it can deliver key insights that can improve supply chain functionality and eliminate friction.
In conjunction with other leading-edge technologies—the Internet of Things (IoT), blockchain and more—agentic AI can help deliver even deeper insights. IoT can provide information on data points like machine health status, asset tracking and production rates. Agentic AI can harness that information and provide actionable insight your teams can use. Elsewhere, secure blockchain databases allow for encrypted data exchange, and can help grant secure, real-time access to all transactions in a vendor database. Here, it can help eliminate the need to manually update and reconcile individual accounting systems.
AI in Action: How Cummins Is Enhancing Sustainability Goals
Power generation and engines OEM Cummins sought to reduce the total amount of packaging waste resulting from manufacturing operations. Internal research found that 75% of its inbound materials and goods travelling from or between manufacturing facilities used expendable packaging.
To combat the waste, Cummins launched an RFID and AI solution to track returnable transport items (RTIs), all powered by Surgere.
The program works like this: With RFID tags on each RTI, as well as overhead readers at dock doors, Surgere’s cloud-based Interius software can track assets as they move between suppliers and Cummins’ own manufacturing sites. For example, each time a supplier fills a reusable container, they ship it to a Cummins facility, and with an RFID reader mounted at the site, the tag is read as the container leaves the supplier’s facility. Cummins then has access to that data indicating what filled containers are on their way via Interius. When the containers arrive at the destination facility, the tags are read again, updating the status of each container. Once containers are emptied, they can be shipped to one of the company’s container management centers where they are cleaned, maintained or repaired, and made available for reuse. The RFID tags are read at these sites when they arrive and when they leave on their way to a supplier to be reused.
The company has realized some significant benefits, including:
- Lower rate of asset damage
- Labor savings by eliminating the need for visual identification of each item
- Optimized fleet sizes based on packaging shipments
- Fewer supply chain bottlenecks
Through the program, Cummins expects to eliminate 84 million pounds of corrugated material, wood and plastic waste annually.
Supply Chain Success Requires Continued Innovation
Your production lines may be running fine and your supply chain tools may be adequate, but in manufacturing, few things are more constant than change and unforeseen complications.
It’s not worth getting left behind. Agentic AI digs deeper into a larger mine of historical data than traditional systems to reveal new insights and empower more accurate predictive analyses. Better forecasting means less risk of excess inventory and wasted production resources. It can also help you better understand your customers, enabling you to amplify your strengths, provide more precise services and identify new business opportunities.
Your team will be better informed to make important decisions and explore newly discovered possibilities. In short: Integrating agentic AI into your manufacturing supply chain ultimately helps you get the most out of the talented humans who make your business possible.
