AI in Supply Chain: Practical Applications and Industry Use Cases

Key takeaways

Supply chain organizations use various types of AI in supply chain operations, including generative AI, agentic AI, and collaborative robots (cobots).

• Artificial intelligence in the supply chain market will likely reach a valuation of $51.12 billion by 2030 [1].

• Implementing AI in supply chain operations is creating an evolution within the industry, enabling you to optimize a wide range of tasks and processes.

• You can use AI to support data-driven decision-making within the supply chain, manage inventory levels, and support safe working conditions.

Discover how leveraging AI in supply chains can improve your operations. If you’re ready to start building AI skills, consider enrolling in the AI Foundations for Everyone Specialization from IBM. This four-course series can help you gain job-ready skills in artificial intelligence, without any necessary experience, so that you can learn ways to implement AI in your organization.

AI and manufacturing: Types of supply chain artificial intelligence

Artificial intelligence within aooo manufacturing and the overall supply chain is revolutionizing the industry with advancements in efficiency and productivity. Several steps of the manufacturing process and supply chain benefit from AI tools, including quality control, where AI can identify flaws in products, and predictive maintenance. This helps AI to predict when machinery may need repair before it becomes a more serious issue. Demand forecasting, safety enhancements, and supply chain management are also areas where AI is making a difference.

Generative AI (GenAI), virtual and augmented reality, and cobots are specific types of artificial intelligence that manufacturers and supply chain managers are capitalizing on. The impact of each of these technologies presents itself in the following ways:

• Generative AI: During the manufacturing process, GenAI helps manufacturers develop multiple variations of a product design, improving product development and enabling the creation of innovative solutions and designs.

• Agentic AI: Capable of functioning independently and with specific types available depending on the task, agentic AI can help manage your logistics, customer service requests, and inventory control tasks.

• VR/AR: Virtual and augmented reality in manufacturing gives employees the ability to train with manufacturing equipment, virtually, helping to reduce the cost of training, while making the training process more efficient.

• Cobots: Cobots can help complete physically challenging or precision-intensive tasks, improving productivity and quality during manufacturing.

Use of AI in supply chain management

AI is useful for a wide range of positions within supply chain management, whether you’re a decision maker, assembly line worker, inventory control analyst, or manufacturer. Business leaders tasked with making difficult supply chain decisions can use data provided by artificial intelligence to make informed, data-driven decisions. If you’re working on the assembly line, artificial intelligence means you get to experience a safer work environment, where computer vision tools can identify risks and ensure your workplace is meeting OSHA regulations. 

How is generative AI reshaping supply chains?

Generative AI is reshaping supply chains in many ways, including by streamlining documentation to ease administrative burdens. Companies can utilize this technology to optimize various aspects, including planning and warehousing, as well as improving the customer experience and human resources. It can also assist you when managing inventory levels by analyzing data, promote communication with customers through chatbots, and accurately predict demand forecasts.

Real-world artificial intelligence in supply chain examples

Artificial intelligence can have a positive impact on supply chain processes across various industries. It can support specific tasks, such as managing storage conditions during food transport or analyzing hospital medicine supply to ensure healthcare providers always have what they need to treat patients. If you’ve ever wondered how Amazon can get packages to your door so quickly, you can thank AI. Amazon uses artificial intelligence to forecast product demand and provide accurate delivery instructions. Using Wellspring, a generative AI model, Amazon provides delivery drivers with precise location information to assist with more complex deliveries in areas where navigation apps may lack support. 

Another major global company that’s deployed AI technology to optimize its supply chain is Walmart. Using tools like agentic AI, Walmart improved its ability to manage inventory, reduce waste, and predict demand as it operates its global supply chain. Walmart can even utilize AI to learn about trending products, identify what customers want, and add them to their shelves.

Pros and cons of pairing AI and supply chain management

Implementing AI for supply chain management comes with several advantages, allowing you to better manage risk, automate processes like data analysis, and provide customer support. Ultimately, this allows your supply chain to function more efficiently while simultaneously lowering costs and equipping you to solve complex problems.

It’s also important to consider specific challenges that can arise when using artificial intelligence. For example, your organization needs to be ready for AI, meaning any plan being put in place must be thought out and strategically implemented based on your needs alongside the capabilities of the technology. Additionally, using AI can raise ethical considerations, such as where you source your data, how you use it, and the measures you employ to ensure its security.

What is the future of AI for supply chain optimization?

Using AI for supply chain optimization is only going to continue to increase, with a projected 38.9 percent collective annual growth rate from 2024 to 2030, resulting in a $51.12 billion industry by 2030 [1]. In the future, AI in supply chain optimization will become progressively more sophisticated and efficient, improving sustainability and learning to operate autonomously on complex tasks. 

How to get started in supply chain management AI

To begin your journey into the supply chain management industry, consider earning a degree such as a bachelor’s in supply chain management or business administration. You can start your career in roles such as supply chain analyst, warehouse operator, or logistics coordinator before advancing to a supply chain manager position. 

However, if you want to learn to implement AI in your existing supply chain management career, consider developing skills and knowledge in artificial intelligence. Focus on building key skills in areas such as machine learning, prompt engineering, and programming languages like Python and Java. Then, you can take a closer look at processes within your workplace to identify opportunities where AI can solve problems and improve workflows.

Read more: 7 Major Supply Chain Trends

Explore our free artificial intelligence resources

Interested in learning more about AI and how you can use it in your career? Check out some of our free resources, like our LinkedIn newsletter Career Chat, and the following tools to continue learning more:

• Watch on YouTube: AI Quick Tip for Supply Chain: Enhancing Efficiency with Predictive Analytics

• Take the quiz: Which AI Course Should You Take? Find Out in 1 Minute

• Hear from an AI expert: AI Problem-Solving Tactics: Expert Insights from Vanderbilt’s Dr. Jules White

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