The Role of AI in Supply Chains
As supply chains become ever more complex, more and more businesses are turning to AI as the solution; in fact, a recent MHI report found that while only 17% of businesses are already using AI, around 45% predicted that they’ll integrate AI in their supply chain by 2027. The report also found that nearly 50% of companies in 2022 believe AI has the potential to disrupt supply chains and create a competitive advantage.
Artificial intelligence (AI), or the use of machines to perform tasks that would otherwise require human intelligence, is increasingly being integrated in supply chains to help managers increase control over supply chain operations at every tier. The main goals of AI in supply chain management are:
- To gain increased supply chain visibility
- To forecast potential outcomes or disruptions
- To find patterns in data that provide actionable insights and inform decision making
- To automate processes within the supply chain
AI can be integrated into nearly every area of the supply chain, from raw material procurement to the distribution of final products to customers. All of AI’s uses in the supply chain work together to help increase transparency, efficiency, flexibility, and, of course, revenue.
In this article, we’ll review why AI is useful in supply chain management and how to implement AI in your supply chain, and explore a few examples of leading companies using AI in their supply chains today.
The benefits of AI in supply chains are numerous and will continue to grow. Here are a few ways businesses currently benefit from implementing AI tools in their supply chains.
AI is frequently used in supply chains to make accurate, data-based predictions. AI-driven demand forecasting is more accurate than manual predictions, allowing supply chain managers to:
- Optimize inventory levels to meet consumer demand and maintain safety stock while reducing storage costs
- Ensure optimal inventory levels across geographic regions
- Forecast optimal amounts of raw material sourcing to reduce waste
- React preemptively to potential changes in demand
AI’s forecasting capabilities allow for reduced costs and reduced disruptions, such as long waiting periods for customers or overstocks. For example, furniture-giant IKEA has begun using AI to more accurately forecast demand across 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.
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 over 20,000 US companies with second-tier suppliers in the country, before it even occurred. These types of AI tools help companies understand and prepare for risks before they cause major disruptions.
Not only do AI’s forecasting capabilities help you stay ahead of disruptions, but AI can also help you react faster when problems do arise. For example, AI can help notify you in seconds of all kinds of disruptions, from fire and flooding to cyber attacks, allowing you to fix the issue and minimize damage.
For companies that regularly deal with large amounts of compliance paperwork, AI can be a promising time-saving tool, as it can help compare information to product specifications or compliance laws. AI also helps detect problems in manufacturing or other stages that may lead to non-compliance, and can analyze workplace safety data to detect potential risks. Finally, automated manufacturing or warehouse processes help to ensure a standardized product quality that complies with regulations. Many companies choose to use a supplier quality management software system in tandem with AI tools in order to ensure high quality products that have gone through multiple stages of QC checks.
AI plays a large role in automation, or the performance of supply chain activities that would otherwise need to be done manually, and thus 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 the efficiency of activities in nearly every step of the supply chain.
As discussed above, AI’s planning ability also helps to reduce disruptions that hamper on-time production and delivery. This may include identifying the most efficient distribution routes or ensuring sufficient inventory.
Better planning, increased efficiency, and automation results in reduced costs throughout the supply chain. In fact, a 2019 survey found that 61% of companies that incorporated AI in their supply chain decreased costs, and more than half increased their revenues. AI-driven reductions in waste, identification of places in the supply chain that are not as productive as they could be, and happier customers all lead to increased profits.
There are several challenges that accompany the implementation of artificial intelligence in the supply chain.
- High initial investment costs: Although costs are dropping as this technology matures, AI implementation currently requires the right hardware, software, and specialists 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 in AI technologies upfront.
- Training and hiring costs: Part of implementation costs include training employees to use new AI-enable tools and/or hiring new employees with the skills to use these tools properly.
- Compatibility: Within supply chains AI has specific use cases, which makes solutions particularly applicable to some types of supply chains and not-yet applicable to others. In the next section we’ve provided a few questions to help you evaluate how applicable current AI technologies are to optimizing your supply chain.
Questions to ask when considering adopting AI technologies for your supply chain:
- Evaluate your current supply chain: Where are the pain points in your current supply chain? What is going well?
- Set concrete goals: What are your goals? What AI technologies can you leverage to best support these goals?
- Review estimated returns on investment (ROI): What are the estimated costs of implementing AI technology? What are the estimated savings?
- Define tracking metrics: How will progress towards these goals be measured?
- Prepare your team: Is your team capable of this transition? Do you need to bring in third-party IT experts?
- Plan for the future: Is your AI plan scalable? How can you plan for continuous improvement?
Innovative companies around the world are using artificial intelligence to gain a competitive advantage. Here are a few ways leading brands are using AI in their supply chains.
Amazon is famous for its fast delivery, from same-day delivery to getting groceries delivered within hours. This speed is largely made possible with AI used to forecast where inventory should be stocked in order to meet customer demand, which is also predicted using AI. While many companies today use AI, Amazon is one of the best examples for how integrating AI into every single step of their operations, from their website to delivery, greatly increases efficiency.
The Home Depot, one of the world’s leading home improvement retailers, was one of the first major retailers to make use of cloud-storage and AI technology for its website and supply chain as a whole. This was particularly important when the COVID-19 pandemic began causing shortages of inventory, and clients began competing for limited resources. Home Depot responded by using AI tools to make decisions about how to move inventory and to analyze consumer data in order to predict demand. Home Depot was better equipped to accurately tell customers whether an item was in stock, when it would be restocked, and when purchases would be delivered.
Delivery-service company UPS uses an AI-powered model to ensure that their transportation routes are as efficient as possible in order to reduce fuel usage. Their ORION (On-Road Integrated Optimization and Navigation) system uses an algorithm to reduce right turns, which saves around 10 million gallons of fuel each year and reduces their carbon emissions by 100,000 metric tons (equal to the emissions of about 21,000 cars).
While famed car manufacturer BMW uses AI throughout their supply chain, one of the most impactful places AI is used is to ensure their cars meet quality and safety standards. Their AI-powered object recognition system reviews photos and then compares these images to cars in production, identifying whether the car has been manufactured correctly. BMW also uses AI to monitor conditions in their production plants to ensure that the environment is suitable for their sensitive equipment. In this way, BMW can detect problems earlier and respond to them faster.