Even the sturdiest supply chains are vulnerable to seismic shocks, whether due to groundbreaking technological advancements, geopolitical shifts, or global crises. Amid these sources of turbulence, artificial intelligence (AI) can be a game-changer, offering a source of rapid response and sustainable solutions to keep supply chains strong.

Recently, Fast Company, Inc and SAP organised a panel of experts convention, discussing the convergence of AI and supply chains. The conversation explored AI’s potential for building more robust supply chains, as well as the challenges companies need to consider as they lean on technology to maximize efficiency and procurement efforts. Here are four takeaways from that conversation.

1. Reduce risks by tracking trends

Supply chain professionals have to keep a lot of plates spinning as they work to mitigate supply chain risks in real time. “You can’t keep up with everything,” said Walter Sun, SVP and global head of AI at SAP. AI can help by tracking news, events, and relevant issues that may have a material impact on supply. AI can also analyze this data to help predict the potential for minor supply chain hiccups—or major catastrophes.

“Predictive analytics is impacting many parts of the supply chain, specifically procurement,” said Eva Ponce, executive director of the Omnichannel Supply Chain Lab at MIT. Predictive analytics enhances procurement by forecasting demand, predicting supplier performance, pricing trends, and optimizing inventory monitoring and performance. A data-driven approach enables organizations to make informed decisions and improve overall efficiency and cost savings. “[It’s] almost like you have a human assistant sitting next to you who could alert you to things you otherwise wouldn’t have known about,” Sun said.

Supply chain planners can also use generative AI to manage daily tasks, such as writing emails to vendors to request updates. Doing so frees up time to focus on more important issues, such as tracking and crisis management.

2. Prepare for multiple outcomes

AI tools can predict trends in demand based on external factors, such as market patterns and weather data. While the use of machine learning in forecasting is nothing new, advancements in AI technology will only make it more powerful—and leave supply chain managers better prepared. “An accurate forecast has been an obsession for supply chain professionals,” Ponce said.

While AI tools that analyze historical data and identify likely outcomes can help ensure more accurate inventory levels, reduce waste, and minimize shortages, it’s not a crystal ball. Ultimately, there’s no way to know which potential outcome will occur, so it’s important to plan for more than one.

Events such as the pandemic-induced shortages or the Suez Canal blockage, which delayed worldwide shipping for months, can cause disruptions that are difficult to plan for. Beyond analyzing simple historical patterns—sales during seasonal holidays in the U.S., for instance—AI can model several “what-if” scenarios based on hundreds of data points. “As soon as one of [these scenarios] does happen, you can have a mitigation plan ready immediately,” Sun said.

3. Personalize the customer side of the equation

Sales is a critical part of the supply chain since customers are the ultimate destination for products. To keep customers happy, personalized experiences are becoming essential. In this area, AI can also be a game-changer for strong supply chains. For example, Walmart is launching a new generative AI search feature that allows customers to search for products by use case, rather than by specific product. For instance, shoppers can search for phrases such as “dinosaur-themed birthday party” and receive a list of products tailored to that search.

Chatbots and AI shopping assistants can also provide customers with personalized shopping suggestions based on previous orders, historical data, and current shopping trends. For instance, recommendations are often based on what other customers have bought alongside another product. If someone buys a certain laptop, AI can automatically suggest relevant docking stations or cases. “It saves users a lot of time,” Sun said. Easy transactions like these can help develop loyal customer relationships and drive demand.

4. Be thoughtful about the AI rollout

Incorporating AI for supply chain management requires careful planning. “One of the most common reasons I have seen companies fail when implementing disruptive technologies like AI is when they are rushing, with a lack of clear vision,” Ponce said.

Start by determining how AI implementation will align with broader business goals, such as driving efficiency, reducing risk, and better time management. Next, evaluate your company’s existing technology assets. As Ponce put it, the questions you should be asking are, “What is the current state of [your] AI capabilities, and how ready is the IT infrastructure to support AI deployment?” Then, identify the tools and technology your company needs to fill in those gaps.

Another factor to consider is the skills and talent required to develop, deploy, and maintain AI solutions. Some organizations will need to hire new talent to do this, but all companies should help employees upskill and stay competitive in the ever-changing field of AI. “Being ready and having the right skills for this journey is key,” Ponce said.

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This post is based on a publication by FastCompany.com