AI & ML technology integrations provide broad advantages for supply chain management. 

By emphasizing digitalization, predictiveness and autonomy, new levels of success in speed, accuracy, service and revenue can be realized. 

The progress of supply chains in adopting AI varies widely. So does the return on investment. But according to one recent study, there’s one strategy that guarantees failure: doing nothing.

Proactive intelligence enables you to balance the fine line between cost and resilience, says Brandon Daniels, chief executive officer of Exiger.

The funds will be used for 10 separate projects across five ports, including cargo route optimization, emission reductions, and trucking appointment systems.

Predictive AI models will power smarter inventory distribution, greater pick path efficiency and dynamic order grouping, thereby improving accuracy, reducing costs and accelerating throughput.

Tom Moore and Keith Moore, CEOs of, respectively, ProvisionAi and Autoscheduler.AI, talk about how AI is helping to solve problems in supply chains — and where it's more a matter of hype.

Kate Vitasek, faculty member at the University of Tennessee, explains how collaborative bidding can bring about a whole new way of looking at supplier-buyer engagements.

How can supply chain leaders implement a sense of predictability in an unpredictable market? By investing in talent and technology, such as artificial intelligence, that can support modern-day challenges.

AI promises to save effort and time on a scale never before witnessed in human history. But to quote Serena Williams: “Everything comes at a cost. Just what are you willing to pay for it?”