It’s near the end of 2025. Just about everyone is talking about Artificial Intelligence (AI) and how technology firms are racing to capitalise on it.
Executives want AI to be integral in just about every business area. That includes supply chains.
Aside from all the automation firms are installing into their operations, executives are aiming to use AI to run supply chains. They believe it is destiny that AI would practically be at the core of most, if not all, supply chain operations.
Supply chains deal with tangible items, principally products & services. As much as AI will soon be capable to running supply chains, executives would still need structures & systems to provide the framework for AI to succeed.
Questions for executives to address include:
- Are existing supply chain systems & structures ready for AI?
- And if not, who will be the people who will set up those systems & structures?
- And how would executives know if the set-ups are done right?
AI is a data-based instrument which learns, answers questions, and makes decisions based on available information. It would, therefore, rely on what resources, systems, and structures presently exist before it presents results.
This means systems and structures need to be set up with clarity. Items, for example, should match what are in the inventory databases to what are actually there. One cannot have an item that exists on the factory floor but isn’t there on the inventory record.
Artificial Intelligence programs would be not much different from traditional supply chain software in requiring the input of details of systems & structures such that the output of results would be most relevant for stakeholders.
For some enterprises, this can be a big chore as it would often be the prerequisite for AI to succeed. Tasks include creating master databases for items, parts, & components and the intricate mapping of processes.
Expertise in engineering may be needed to not only point out the technical details of operations but also validate the methodical procedures which many may find out they didn’t even know about.
Many software projects have fallen by the wayside because at the very start, the input of information didn’t match what was happening in real life.
In any endeavour, there is often so much pre-work which needs to be done.
AI would be no exception.
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