Five AI Use-Cases in Supply Chains

Apple is Stuck Between a Rock and a Hard Place

While Apple designs its products in the U.S., most of their products—such as iPhones—are mostly made in China, where Apple has built a huge supply chain over the past few decades.

As the current US administration threatens to impose high tariffs on many Chinese goods, and while smartphones were recently exempted, Apple may still be at risk of tariffs.

Apple’s deep supply chain integration in China has helped it grow but now ​makes it vulnerable​ as tensions rise between the U.S. and China.

Although there’s talk of moving production to the U.S., experts say this is unrealistic, and most Apple products will likely continue to be made in Asia.


Five AI Use-Cases in Supply Chains

Google recently published​ a report on how companies are implementing AI in real-world business use-cases. Here’s five AI use-cases in Supply Chains:

BMW Group, in collaboration with Monkeyway, developed the AI solution SORDI.ai to optimize industrial planning processes and supply chains with gen AI. This involves scanning assets and using Vertex AI to create 3D models that act as digital twins that perform thousands of simulations to optimize distribution efficiency.

Kinaxis is building data-driven supply chain solutions to address logistics use cases including scenario modeling, planning, operations management, and automation.

Prewave, a supply chain risk intelligence platform, utilizes Google Cloud’s AI services to provide end-to-end risk monitoring and ESG risk detection for businesses. This enables companies to gain transparency deep into their supply chains, ensuring resilience, sustainability, and compliance with regulations like the European CSDDD.

Nowports is harnessing the power of AI to revolutionize logistics and stand out from the competition. By analyzing key operational information, they aim to accurately predict market behavior, optimizing their entire supply chain.

NetRise developed Trace to provide software supply chain security by introducing AI-powered intent-driven searches; these allow users to search their assets based on the underlying motives or purposes behind the code and configurations, rather than solely relying on signature-based methods.”

​You can read the full report here​.


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