I am the Vice President of Supply Chain Services at ARC Advisory Group, a leading industry analyst and technology consulting company. I engage in quantitative and qualitative research on supply chain management technologies, best practices, and emerging trends.
While Generative AI has sparked great excitement, a form of artificial intelligence called Causal AI might offer much greater potential. Causal AI offers the tantalizing promise of being able to unravel the intricate web of cause-and-effect relationships that govern business operations. Georgia-Pacific has pioneered the application of Causal AI to achieve touchless commerce.
IT systems can be part of the problem. The complexities associated with an enterprise resource planning system’s available-to-promise functionality can lead an ERP system to get hung up, requiring time-consuming human intervention before an accurate promise can be relayed to customers.Available-to-promise functionality seeks to ensure a company has the requisite manufacturing and logistics capacity to deliver an order to a customer on the date they want it.
According to Mr. Carroll, when the system “can’t perform an autonomous decision, the system will provide recommendations on how it would solve the problem and then explain to the employee why it is giving that recommendation. The employee can then validate the system’s recommendation or make changes to it. It’s a different way of working.”GP describes Causal AI as a mixture of Knowledge AI and Data AI.
Causal AI Influencing Attributes
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