Michael Barnett makes the case for using AI to improve supply chain performance, identifies how it can be used, and provides a couple of examples.
It remains too rare for companies to see tangible improvements in supply chain performance from efforts to embed data and AI in their processes. Based on the latest research, ~30% of digital supply chain transformations deliver value even for the largest, most mature supply chain organizations (1). It is no wonder that so many leaders are skeptical of the latest advancements in AI and instead focus on traditional performance improvement and operations excellence methodologies to solve their problems.
If that is the case, then why is now the time to embed data and AI into the supply chain? The answer: two significant advancements in technology are converging to rapidly shrink the gap in an organization between its AI capabilities and the problems which need solving.
Before we discuss these advancements, it is important to level-set on the definition of “AI,” which is increasingly only referring to “Generative AI” in most discussions today. In this article, we view AI in two distinct ways:
AI is a capability that supply chains can leverage to solve problems (similar to OpEx methodologies), and not a solution that a 3rd party will come implement in the business
AI is inclusive of various techniques, not just GenAI, which generate value from data:
Key points include:
- How the “tech stack” is transforming
- Why GenAI co-pilots are disrupting solution development
- Flexible and advanced capabilities
Read the full article, Now Is the Time to Embed AI in Your Supply Chain, on LinkedIn.