Artificial intelligence (AI) is creating unparalleled new opportunities for logistics and supply chain management, recent reports show. However, many organizations remain uncertain about how best to implement it.
“AI is a moving target,” said Chris Caplice, executive director of the MIT Center for Transportation and Logistics. “It’s not sitting still; it’s aspirational because what was considered AI 30 years ago—even 20 years ago—is not considered cutting-edge AI anymore.”
In considering how to implement AI, managers need to understand how different analytic approaches, such as traditional AI, generative AI and operations research, work together, Caplice said.
Caplice and Lior Ron, founder and CEO of Uber Freight, discussed the analytic tools being used in supply chain management, the logistical problems AI can help solve and other managerial benefits of using AI in logistics.
AI technologies are poised to solve many challenges faced in logistics, Ron said.
These include:
- Fragmented supply chains and the need to connect networks to optimize and drive better outcomes.
- Market volatility, particularly changes in pricing and disruptions in services.
- Safety concerns, including those related to COVID-19, driver safety and digital fraud.
- The impact that trucking and freight have on climate change.
Innovations that address some of these challenges are emerging now. For example, Uber Freight has used machine learning to pioneer algorithmic carrier pricing, which ensures that carriers receive upfront guaranteed pricing for trucking and freight. “By looking at hundreds of different parameters, we’ve been able to make [this model] accurate enough to introduce a marketplace that is now removed of all the friction, guessing and back-and-forths [of] trying to estimate pricing,” Ron said.
Uber Freight is also using machine learning to address vehicle routing, a complex issue that involves determining the most efficient route for a vehicle to deliver goods to a set of locations.
