AI in Supply Chain – Some Definitions


If we are going to invest in AI and Machine Learning technology with the goal to improve our Supply Chain performance, we must have a working knowledge of just what AI/ML is.

The media is filled with stories about AI. But there is scant information related to AI for the Supply Chain. Looking for some clarity? There are plenty of obtuse definitions on the web, but almost none of them tell you what AI does for Supply Chain. These definitions will.


AI is an umbrella set of technologies, from robotics to analytical systems. Within AI we have various subgroups such as machine learning, deep learning, natural language processing, robotics, and so on.

We hear and read over and over that AI is a technology designed to work like the human brain. No, No, No! That is not exactly right. The smell of fresh rain. The feel of those 400 thread count sheets. The taste of fresh hot bread and butter. The sense of accomplishment. These are all processed by the human brain. Of course, in the broadest sense, creating a way for a machine to mimic these responses is a goal of AI, but we know the actual organic experience and emotions stored about these experiences is very different from digital information.

Part of the problem with the public definitions is they don’t really work for Supply Chain. And so much of the press is about consumer apps, call centers, HP systems, etc. For our purposes, as supply chainers who are actually trying to decipher what AI2
is—what it’s good for and why we need it—we require practical definitions.

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