How is the Logistics and Supply Chain Field Benefiting from AI?

AI in the supply chain has many applications, not least of which includes logistics. While historically logistics teams may have operated in siloes and relied on manual, labor-intensive processes, they are now leaning into AI-powered technologies to gain greater visibility into their operations and process data at lightning speed. As these technologies advance and evolve, logistics and supply chain teams will only continue to witness the benefits of effective AI integration in their operations. 

How can AI be applied to supply chain activities? 

You don’t need to look very hard to find potential benefits for AI in the supply chain and logistics. The technology can be applied through such activities as demand planning, demand forecasting, customer service, inventory management and optimization, warehouse management, labor, and more.  

For example, Tyson Foods is using a supply chain control for its logistics and inventory that serves an aggregate of insights, KPIs, and AI-driven recommendations, and the company has plans to expand it to other areas. Having access to insights that are nearly real-time is expected to fuel more informed and timely decision-making, says Adam Clark, VP of IT business shared services. “These KPIs span demand and supply planning, distribution operations, network optimization, food safety, and team member safety.” 

How does artificial intelligence improve supply chain?

For CPGs, there are many potential benefits of AI in the supply chain. Ways that the technology can improve operations include (but aren’t limited to):  

• Predicting when factory equipment might require maintenance so companies can be more proactive about repairing and replacing them
• Identifying when machinery isn’t being properly optimized in order to reduce energy waste
• Identifying patterns in customer service complaints to in turn identify problems in product manufacturing 
• Optimizing labor scheduling to improve employee efficiency and satisfaction 

How can AI enhance sustainability in supply chains?

The impact of AI in supply chain can be profound, and the technology has the potential to play a leading role in supporting sustainable supply chains thanks to its ability to help organizations better predict demand. Fewer products made means fewer products tossed. Similarly, having visibility into the amount of resources actually required for production means companies can reduce the amount of time machinery is operating unnecessarily and even predict when equipment might break down. 

“As companies are trying to align their corporate sustainability goals with supply chain sustainability goals, AI can be used to help with creating more scenarios to consider in order to fulfill customer needs while still adhering to objectives for sustainability,” Amber Salley, senior director analyst at Gartner, tells CGT.  

Indeed, high-performing supply chains are 19% more likely on average to have capabilities in place to achieve their sustainability goals, according to the research firm.  

“Through digital transformation … and making it visible and usable through analytics or artificial intelligence in real-time to all parties that need it, organizations can make faster and better decisions that lead to improved business and sustainability outcomes, such as the rightsizing and appropriate allocation of inventories and the reductions in fuel, energy, packaging, and other material usage,” affirms Jordan Speer, IDC research director of product sourcing, fulfillment, and sustainability. 

For example, Unilever reports that it’s using IoT control devices and artificial intelligence to improve its energy efficiency. The supply chain technology is enabling it to identify factory floor production changes so it can take action on sources of waste heat and/or shut down machines when they’re not necessary. 

The company has reduced electricity usage by 10% in its Port Sunlight factory in the U.K. by using IoT to monitor what’s happening on the factory floor in real-time, according to Reginaldo Ecclissato, Unilever chief business operations and supply chain officer. The info is sent to the cloud and notifies line leads about machines that have been left on for two hours with no production.

Within the last mile, organizations can optimize asset use and smart routing using intelligent automation and/or AI to optimize delivery routes and vehicle capacity utilization, notes Speer. This can reduce vehicles on the road and the distances they travel to trim costs and carbon emissions alike. 

What are some disadvantages of artificial intelligence? 

As with all technologies, there are a host of challenges of AI in supply chain. Some of these include: 

• Organizations must have a large amount of data for the technology to identify patterns and learn from the insights. This is particularly true for the machine learning subset of AI. 
• Their employees must have the right skill sets and mindsets to properly leverage the technology. This may require upskilling employees or retaining new talent. 
• AI carries a host of ethical considerations, including the potential for bias and misuse of information. The rising popularity of generative AI has brought the importance of responsible AI to the forefront of these conversations. 

To tackle this last, and very important piece, Reggie Townsend, VP of data ethics at SAS, offers this advice: “At the very top, before you start writing a line of code, [you have] to activate a trustworthy AI environment. You've got to start with some measure of oversight. You’ve got to think about what your operation is going to look like. You've got to make sure you've got adequate performance and risk mitigation in place, and you've got to work on building a culture that is ethical by design.”