AI in Supply Chain Management: Transforming the Industry

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With the pandemic and its subsequent disruptions, we have seen the enormous impact of uncertainties on supply chains and the need for companies to have smart contingency plans to deal with them. Is AI the key to solving this problem?

By incorporating AI in Supply chain, companies can improve capacity planning, demand forecasting, productivity, and efficiency, while also lowering supply chain costs and increasing output.

Over the next five years, Gartner predicts that supply chain organizations will double the level of machine automation in their processes. Let’s discuss how AI is being used in supply chain and its advantages and drawbacks, as well as its future.  

AI in Supply Chain: An Overview

A supply chain management system includes supply chain, logistics, inventory management, and storage. Many smaller processes and interactions make up the supply chain.

These processes offer tremendous opportunities for Artificial Intelligence-driven supply chain management. Businesses operating in the SCM space consider AI to be the holy grail because of its ability to automate, augment, and enhance customer experience, decision-making, and company strategies.

Supply chain and logistics industry can benefit from machine learning (ML) because it automates many mundane tasks and enables companies to focus on more strategic and impactful activities. To better understand AI for supply chains, here are some examples of how Artificial Intelligence is being used in supply chains.

Examples of AI in Supply Chain and Logistics 

The following are four examples of how Artificial Intelligence in supply chain management makes a positive impact.

Customer Service Using Chatbots

As chatbots gain popularity, it is harder to ignore the role of AI in logistics, B2B marketing, and procurement processes for supply chain companies. That’s why many companies use Artificial Intelligence to automate customer service tasks. Most customers have similar concerns and questions that involve similar solutions. Hence, an AI for customer service has plenty of data to draw from and address customer concerns.

The customer representatives can, therefore, focus on complex customer problems and requests outside the scope of your typical AI, instead of answering the same questions over and over again. Using AI software development and ML services, you can build AI chatbots for your business to automate customer service.

Predicting Demand

It is a common joke that we are stalked by the algorithms that are responsible for targeted advertising. In reality, human behavior can be predicted. Companies are using AI to predict customer demand more accurately, enabling them to optimize production and reduce inventory costs.

For instance, Unilever utilizes AI to forecast demand for its products, reducing inventory costs by 15% and improving customer service. The goal of demand forecasting in supply chain management is to predict what will be needed when and where and even forecast shortages in advance. In turn, this reduces inventory losses and prevents out-of-stock situations.

Warehouse Automation

Warehouse operations, like picking, sorting, and packing, can be automated with AI-powered robots. Because robotic systems can operate 24 hours a day, seven days a week, this technology not only reduces labor costs but also improves accuracy and efficiency.

AI is utilized in many warehouses, such as Amazon Fulfillment Centers, to automate various tasks. Using this system, the AI predicts where robots and humans will be, and organizes their activities accordingly. All of this results in workers spending less time traversing the warehouse and more time getting products to where they need to be, whether that is for storage or shipping.

Predictive Maintenance

Predictive maintenance is one of the most significant parts of AI in supply chain. With AI algorithms, companies are analyzing sensor data to predict when equipment is likely to fail, so they can schedule maintenance proactively before further problems arise.

Thus, companies can minimize the risk of unplanned downtime and increase overall efficiency by preparing for machine downtime.  As an example, Schneider Electric used Artificial Intelligence to predict equipment failures, which reduced maintenance costs by 25% and unplanned downtime by 20%.

AI in Supply Chain: Key Benefits

There are many benefits of AI in the supply chain and logistics, let’s have a look at the significant ones in detail.

Provides Advanced Supply Chain Insights and Data

The supply chain can benefit from AI by using data that is near-real-time. By using it, companies can save time and money, reduce waste, and increase efficiency. Having real-time information about inventory levels and stock locations allows businesses to respond intuitively.

With this information, companies can make quick decisions about how much stock they have at each location without having to wait until the end of the month or quarter. Supply chain scheduling is essential to planning the delivery of goods at particular times and days. Businesses can also make better decisions using insights gained from supply chain analytics.

Reduces Operational Costs

AI in supply chain can reduce operational costs by analyzing data and deciding which actions are necessary. It facilitates the automation of processes that would otherwise require human intervention. In the supply chain, Artificial Intelligence can save companies money without compromising performance.

Speeds up Shipping

With logistics software solutions, you can determine which routes your trucks should follow, how quickly they should travel along those routes, and when they should arrive. Data generated by supply chain operations can provide these insights. As a result, it can be used to predict where demand will be highest and prevent one location from being overloaded with shipments or running out of stock for too long.

Ensures Safe Warehouse Operations

In supply chains, AI is widely used to ensure safety throughout the supply chain operation. The use of sensors and cameras facilitates a more efficient and safe workflow.

Sensors, for example, can detect when a pallet jack or a forklift has been left unattended, so workers can retrieve it quickly. It prevents accidents caused by a lack of supervision. Keeping an eye on the temperature in your warehouse can also help you avoid fire incidents if the temperature rises too high.

Optimizes Storage Efficiency

The use of AI in the supply chain gives you a better idea of how much space you’ll need for storage, how long it’ll take to move items, and what kind of equipment you’ll need. In addition to helping you determine which products fit best in different shipping containers, these systems can also tell you how many boxes each product needs to be shipped.

AI Supply Chain – What are the Disadvantages?

AI can have many advantages in supply chains, but it also has some drawbacks. The following are some disadvantages:

Artificial Intelligence in supply chains has the potential to make mistakes as a result of algorithms that run on computers. Algorithms trained on bad data might not recognize problems with their analysis if they were trained on bad data.

A trained algorithm might not work properly if it is applied to data from another period. This is because the two periods differ.

AI also has the disadvantage of not always accounting for human error or unpredictability in the supply chain.

Thus, even if an algorithm appears to work perfectly when tested against historical data, it may fail in real-time situations where humans interact and make decisions based on a variety of factors such as their moods, emotions, or physical health.

Many people are dissatisfied with the loss of jobs due to automation. Over the next few years, Artificial Intelligence will automate several manual tasks in the supply chain. In some areas, humans may no longer be needed by businesses as a result of this change.

Future of AI in Supply Chain

The field of Artificial Intelligence is still in its early stages. We will see many more advancements in this industry as it matures. In the coming years, there will be significant changes. 

According to Gartner, we can expect the following trends over the next few years: 

  • Over 75 percent of large companies will employ “intralogistics smart robots” in their warehouses by 2026. 
  • Artificial Intelligence will be embedded in more than 75% of commercial supply chain management applications by 2026.
  • The use of AI-based applications in the supply chain will be embraced by 50% of companies.

This is only a prediction for the next few years. Even so, there seems to be an almost limitless number of possibilities. Currently, companies like Uber Freight are working towards the development of autonomous long-haul vehicles as AI matures alongside smart vehicles.

For those in the logistics and supply chain industries, we can expect to see a push to adopt these new technologies in order to become more efficient and cost-effective. 

Ready to take advantage of AI in your supply chain and logistics business? Get expert AI advice from a software development company to incorporate AI effectively. OpenXcell has experience working in supply chain industry for more than a decade.

Our team at OpenXcell has developed numerous software solutions for supply chain and logistics businesses, and now with AI being widely used, we are helping them integrate AI into their software to automate tasks. Feel free to contact our AI experts for a free consultation. 

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Niha Parmanandani

A dynamic content writer with a degree in Mass Communication and Journalism, she specializes in writing for web and social media.  It is her passion to play with words and keep up with technology trends. Her passion for reading drives her to create engaging, educational, and inspiring content.


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