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Ways to use Artificial Intelligence for Supply Chain Management

Artificial Intelligence and Data Analytics are considered the two most demanded technologies. Gone are the days when we used Excel and Google spreadsheets to manage and analyze data. As per estimates, every single day results in the creation of over 2.5 quintillion bytes of data. Therefore, it has become near impossible to manage data manually. There comes the use of Artificial Intelligence. It’s a given that only machines can process that much data accurately and timely.

Similarly, the huge task of supply chain management becomes a lot more efficient when we deploy AI in it. From the manufacturing department to the delivery department, AI finds its place in almost every supply chain stage. Recent reports indicate that the adoption of Artificial Intelligence in the supply chain results in dynamic logistic systems, smart manufacturing, better inventory management, and real-time delivery controls.

  • 61% of the executives reported decreased costs after introducing AI into their supply chains.
  • More than 50% of executives reported increased revenues.
  • More than 33% of executives reported a revenue increase of more than 5%.

Advantages of AI in Supply Chain Management

  • It reduces manual human work.
  • The near-real-time data enhance end-to-end visibility. Hence, the tracking process becomes all the more efficient.
  • The AI and machine learning-driven predictions as well as analysis of multiple scenarios augment informed decision-making.
  • It provides improved analytic insights based on the customer data and response. This enables better policy and plan formulation in supply chain management.

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Ways to use Artificial Intelligence for Supply Chain Management

In Optimizing Delivery logistics and Routing

The shipment tracking process is cumbersome process when done in conventional ways. But AI-driven GPS tools can out the best plan of delivering and tracking a module of packages in no time. Customers don’t have the earlier level of patience anymore. They expect quick delivery as well as exact tracking of their shipments.

In the Efficient Loading and Unloading process

It takes a great deal of calculation to find out the quickest and the most efficient way of loading and unloading goods on shipping vessels. But this task can be simplified by using AI-driven tools. It provides real-time insights into the loading process by analyzing the software, hardware, and data. This enables optimizing the arrangements inside the trailers to minimize wastage as much as possible.

In Demand Prediction

One of the major uses of AI is in demand forecasting from customer information like purchase orders and feedback. The results produced by AI enable warehouse managers to regulate their inventory stocking. Sometimes excess inventory results in money being locked up in inventory. Therefore regular inventory management is highly recommended.

One such AI-driven tool is C3 AI. It brings forward the detailed report about the raw as well as finished goods in quick time. The advanced service can even recommend the amount of stocking required as per data gathered from supply and demand factors.

In improving the Longevity of vehicles

Machine and vehicle failure can lead to delays and severe outcomes if not detected timely. This is another application of AI. The IoT device data containing the past as well as real-time data can recommend maintenance. They also predict failures.

The platform uses AI to predict a range of mechanical failures timely in machines and vehicles. Hence, it increases productivity, reliability, and security.

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For saving costs and boosting revenue

This includes the AI-driven tools which assess every aspect of the supply chains through a central database. Such tools enable the overall monitoring of the supply chains and pinpointing disruptions at any stage. The supply chain managers can reduce their costs and boost revenue by using such applications.

The most common route for AI into the logistics system passes through the deployment in a platform such as an Enterprise Resource Planning (ERP) system. Then we can add the elements of AI- Machine Learning (ML) and Natural Language Processing (NLP) as per our requirements.


The above-mentioned ways are not the end. In fact, they are the means to a new beginning. Argo AI and Wal-Mart Ford are planning to use self-driving vehicles to deliver goods to customers. Technology evolvement is the only way to sustain the tough current scenario. The supply chain disruptions due to Covid-19 and the geopolitical conflicts have brought several companies to their knees. But the smart ones took the benefit of the situation and adopted the AI-driven technologies in their supply chain management. Indeed, AI represents future business growth.