The role of AI in supply chains
As supply chains become more and more complex, more and more businesses are turning to AI as a solution; In fact, a recent MHI report found that while only 17% of businesses are already using AI, nearly 45% predicted they would integrate AI into their supply chain by 2027. The report also showed that by 2022, almost 50% of companies believe: AI has the potential to disrupt supply chains and create competitive advantage.
Artificial intelligence (AI), or the use of machines to perform tasks that would otherwise require human intelligence, is increasingly being integrated into supply chains to help managers increase control over supply chain operations at every level. The main goals of AI in supply chain management are:
- To gain supply chain visibility
- To predict possible outcomes or failures
- Find patterns in data that provide actionable insights and inform decision making
- Automate processes in the supply chain
AI can be integrated into almost every area of ​​the supply chain, from the procurement of raw materials to the distribution of final products to customers. All the applications of artificial intelligence in the supply chain work together to help increase transparency, efficiency, flexibility and, of course, revenue.
In this article, we’ll discuss why AI is useful in supply chain management and how to apply AI to your supply chain, and explore some examples of leading companies using AI in their supply chains today.
The benefits of AI for supply chain management
The benefits of artificial intelligence in supply chains are numerous and will continue to grow. Here are some ways businesses are currently benefiting from implementing AI tools in their supply chains.
More accurate planning
AI is often used in supply chains to make accurate, data-driven predictions. AI-based demand forecasting is more accurate than manual forecasting, allowing supply chain managers to:
- Optimize inventory levels to meet consumer demand and maintain safety stocks while reducing storage costs
- Ensure optimal inventory levels across geographic regions
- Predict optimal supply quantities of raw materials to reduce waste
- Proactively respond to potential changes in demand
The predictive capabilities of artificial intelligence allow you to reduce costs and reduce disruptions, such as long customer waiting periods or excess inventory. For example, furniture giant IKEA has started using AI to more accurately predict demand in their 450 stores and 54 destination markets. Their demand sensing tool uses over 200 data sources to make statistical predictions about when and where specific products will be in demand. The company reports a 98% accepted forecast.
Reduced disruption
AI can be used extremely effectively to help you prepare for potential disruptions. For example, Interos, an AI-powered supply chain risk management tool, assessed how Russia’s invasion of Ukraine would affect more than 20,000 US companies with second-tier suppliers in the country before it took place. These types of AI tools help companies understand and prepare for risks before they cause major disruptions.
AI’s predictive capabilities not only help you stay ahead of outages, but AI can help you respond more quickly when problems arise. For example, AI can help alert you to all kinds of disruptions, from fire and flood to cyber attacks, within seconds, allowing you to resolve the issue and minimize damage.
Regulatory compliance
For companies that regularly conduct supplier audits with large amounts of compliance documentation, AI can be a promising time-saving tool because it can help compare information against product specifications or compliance laws. AI also helps identify problems in manufacturing or other stages that could lead to non-compliance, and can analyze workplace safety data to identify potential risks. Finally, automated manufacturing or warehouse processes help ensure standardized product quality that meets regulations. Many companies choose to use a supplier’s quality management software system in conjunction with AI tools to ensure high-quality products that have passed multiple rounds of QC inspections.
Reduced time to market
AI plays a major role in automating or performing supply chain activities that would otherwise have to be done manually, and therefore more slowly, by an employee or supply chain manager. AI-powered technologies such as video or text processing, warehouse robots, 3D printers, or even self-driving cars are all examples of how AI can increase operational efficiency at nearly every step of the supply chain.
As mentioned above, AI’s scheduling ability also helps reduce disruptions that prevent on-time production and delivery. This may include identifying the most efficient distribution channels or ensuring sufficient inventory.
Increasing revenue
Better planning, increased efficiency and automation lead to reduced supply chain costs. In fact, a 2019 study found that 61% of AI companies that incorporated AI into their supply chain reduced costs, and more than half increased their revenues. AI-powered waste reduction, identifying places in the supply chain that aren’t as efficient as they could be, and happier customers all lead to increased profits.
Implementing AI in your supply chain. challenges and solutions
There are several challenges that accompany the implementation of artificial intelligence in the supply chain.
- High initial investment costs. Although costs are coming down as this technology matures, implementing AI currently requires the right hardware, software, and professionals to run and manage it. While the overall savings from AI in the supply chain will likely outweigh these initial costs over time, companies should expect to invest a significant amount of money up front in AI technologies.
- Training and hiring costs. Part of the implementation costs include training employees to use the new AI-enabled tools and/or hiring new employees who have the skills to use those tools properly.
- Compatibility. AI in supply chains has specific use cases that make solutions particularly applicable to some types of supply chains and yet not applicable to others. In the next section, we’ve provided some questions to help you assess how applicable current AI technologies are to optimizing your supply chain.
Questions to ask when considering adopting AI technologies for your supply chain:
- Assess your current supply chain. Where are the pain points in your current supply chain? What is going well?
- Set specific goals. What are your goals? What AI technologies can you use to best support these goals?
- Review estimated returns on investment (ROI). What are the estimated costs of implementing AI technologies? What are the estimated savings?
- Define tracking metrics. How will progress toward these goals be measured?
- Prepare your team. Is your team capable of making this transition? Do you need to engage third-party IT experts?
- Plan for the future. Is your AI plan scalable? How can you plan for continuous improvement?
Examples of successful applications of AI in supply chain management
Innovative companies around the world are using artificial intelligence to gain competitive advantage. Here are some ways leading brands are using AI in their supply chains.
Faster delivery times: Amazon:
Amazon is known for its fast shipping, from same-day shipping to grocery delivery within hours. This speed is largely made possible by artificial intelligence, which is used to predict where inventory should be stocked to meet customer demand, which is also predicted using AI. While many companies are using AI today, Amazon is one of the best examples of how integrating AI into every step of their operations, from their website to shipping, greatly increases efficiency.
Accurate inventoriesHome storage
The Home Depot, one of the world’s leading home improvement retailers, was one of the first major retailers to use cloud storage and AI technology for its website and supply chain as a whole. This was especially important when the COVID-19 pandemic began to cause inventory shortages and customers began to compete for limited resources. Home Depot responded by using AI tools to make decisions about how to move inventory and analyzing consumer data to predict demand. Home Depot was better equipped to tell customers exactly if an item was in stock, when it would be restocked, and when purchases would be shipped.
StabilityUnited Parcel Service (UPS)
Delivery service company UPS is using an AI-powered model to ensure that their transportation routes are as efficient as possible to reduce fuel use. Their ORION (integrated road optimization and navigation) system uses a right-turn reduction algorithm that saves about 10 million gallons of fuel annually and reduces carbon emissions by 100,000 metric tons (equivalent to the emissions of about 21,000 cars).
Quality control: BMW:
While renowned carmaker BMW uses AI throughout its supply chain, one of the most impactful places to use AI is in making their vehicles meet quality and safety standards. Their AI-powered object recognition system reviews photos and then compares those images to production cars to determine if the car was manufactured correctly. BMW also uses artificial intelligence to monitor conditions in their manufacturing plants to ensure the environment is suitable for their sensitive equipment. In this way, BMW can detect problems earlier and respond to them more quickly.